Overview

Dataset statistics

Number of variables257
Number of observations1000
Missing cells159716
Missing cells (%)62.1%
Total size in memory10.8 MiB
Average record size in memory11.1 KiB

Variable types

Numeric1
Text242
Unsupported14

Alerts

year_ending has constant value ""Constant
district_chilled_water_use has constant value ""Constant
electricity_use_generated_2 has constant value ""Constant
estimated_data_flag_district has constant value ""Constant
ambulatory_surgical_center has constant value ""Constant
data_center_pdu_input_meter has constant value ""Constant
data_center_pdu_output_meter has constant value ""Constant
data_center_it_equipment has constant value ""Constant
data_center_it_energy has constant value ""Constant
enclosed_mall_gross_floor has constant value ""Constant
hospital_general_medical_10 has constant value ""Constant
hospital_general_medical_11 has constant value ""Constant
mailing_center_post_office has constant value ""Constant
movie_theater_gross_floor has constant value ""Constant
pre_school_daycare_gross has constant value ""Constant
alert_gross_floor_area_is has constant value ""Constant
alert_property_has_no_uses has constant value ""Constant
third_party_certification_1 has constant value ""Constant
parent_property_id has 964 (96.4%) missing valuesMissing
parent_property_name has 964 (96.4%) missing valuesMissing
nyc_borough_block_and_lot has 32 (3.2%) missing valuesMissing
nyc_building_identification has 69 (6.9%) missing valuesMissing
address_2 has 983 (98.3%) missing valuesMissing
county has 857 (85.7%) missing valuesMissing
national_median_reference has 21 (2.1%) missing valuesMissing
_2nd_largest_property_use has 742 (74.2%) missing valuesMissing
_2nd_largest_property_use_1 has 742 (74.2%) missing valuesMissing
_3rd_largest_property_use has 891 (89.1%) missing valuesMissing
_3rd_largest_property_use_1 has 891 (89.1%) missing valuesMissing
metered_areas_energy has 40 (4.0%) missing valuesMissing
metered_areas_water has 410 (41.0%) missing valuesMissing
energy_star_score has 301 (30.1%) missing valuesMissing
energy_star_certification has 940 (94.0%) missing valuesMissing
energy_star_certification_1 has 940 (94.0%) missing valuesMissing
site_eui_kbtu_ft has 99 (9.9%) missing valuesMissing
weather_normalized_site_eui has 234 (23.4%) missing valuesMissing
national_median_site_eui has 21 (2.1%) missing valuesMissing
difference_from_national has 112 (11.2%) missing valuesMissing
site_energy_use_kbtu has 99 (9.9%) missing valuesMissing
weather_normalized_site_energy has 234 (23.4%) missing valuesMissing
national_median_site_energy has 21 (2.1%) missing valuesMissing
weather_normalized_site has 170 (17.0%) missing valuesMissing
weather_normalized_site_1 has 284 (28.4%) missing valuesMissing
source_eui_kbtu_ft has 99 (9.9%) missing valuesMissing
weather_normalized_source has 234 (23.4%) missing valuesMissing
national_median_source_eui has 21 (2.1%) missing valuesMissing
difference_from_national_1 has 112 (11.2%) missing valuesMissing
source_energy_use_adjusted has 304 (30.4%) missing valuesMissing
source_energy_use_kbtu has 99 (9.9%) missing valuesMissing
weather_normalized_source_1 has 234 (23.4%) missing valuesMissing
national_median_source_energy has 21 (2.1%) missing valuesMissing
fuel_oil_1_use_kbtu has 1000 (100.0%) missing valuesMissing
fuel_oil_2_use_kbtu has 843 (84.3%) missing valuesMissing
fuel_oil_4_use_kbtu has 930 (93.0%) missing valuesMissing
fuel_oil_5_6_use_kbtu has 988 (98.8%) missing valuesMissing
diesel_2_use_kbtu has 996 (99.6%) missing valuesMissing
kerosene_use_kbtu has 1000 (100.0%) missing valuesMissing
propane_use_kbtu has 1000 (100.0%) missing valuesMissing
district_steam_use_kbtu has 874 (87.4%) missing valuesMissing
district_hot_water_use_kbtu has 1000 (100.0%) missing valuesMissing
district_chilled_water_use has 999 (99.9%) missing valuesMissing
natural_gas_use_kbtu has 227 (22.7%) missing valuesMissing
weather_normalized_site_2 has 284 (28.4%) missing valuesMissing
electricity_use_grid_purchase has 120 (12.0%) missing valuesMissing
electricity_use_grid_purchase_1 has 120 (12.0%) missing valuesMissing
weather_normalized_site_3 has 170 (17.0%) missing valuesMissing
electricity_use_grid_purchase_2 has 120 (12.0%) missing valuesMissing
electricity_use_generated has 985 (98.5%) missing valuesMissing
electricity_use_generated_1 has 985 (98.5%) missing valuesMissing
electricity_use_generated_2 has 985 (98.5%) missing valuesMissing
annual_maximum_demand_kw has 968 (96.8%) missing valuesMissing
annual_maximum_demand_mm has 968 (96.8%) missing valuesMissing
annual_maximum_demand_meter has 968 (96.8%) missing valuesMissing
green_power_onsite_kwh has 985 (98.5%) missing valuesMissing
green_power_offsite_kwh has 120 (12.0%) missing valuesMissing
avoided_emissions_onsite has 985 (98.5%) missing valuesMissing
avoided_emissions_offsite has 114 (11.4%) missing valuesMissing
total_ghg_emissions_metric has 57 (5.7%) missing valuesMissing
direct_ghg_emissions_metric has 51 (5.1%) missing valuesMissing
indirect_ghg_emissions_metric has 53 (5.3%) missing valuesMissing
national_median_total_ghg has 23 (2.3%) missing valuesMissing
estimated_data_flag has 59 (5.9%) missing valuesMissing
estimated_data_flag_natural has 175 (17.5%) missing valuesMissing
estimated_data_flag_fuel has 803 (80.3%) missing valuesMissing
estimated_data_flag_fuel_1 has 897 (89.7%) missing valuesMissing
estimated_data_flag_fuel_2 has 942 (94.2%) missing valuesMissing
estimated_data_flag_district has 866 (86.6%) missing valuesMissing
net_emissions_metric_tons has 46 (4.6%) missing valuesMissing
percent_of_electricity_that has 121 (12.1%) missing valuesMissing
percent_of_recs_retained has 985 (98.5%) missing valuesMissing
percent_of_total_electricity has 985 (98.5%) missing valuesMissing
costar_property_id has 1000 (100.0%) missing valuesMissing
leed_us_project_id has 984 (98.4%) missing valuesMissing
ambulatory_surgical_center has 999 (99.9%) missing valuesMissing
automobile_dealership_gross has 1000 (100.0%) missing valuesMissing
bank_branch_gross_floor_area has 980 (98.0%) missing valuesMissing
bank_branch_number_of has 980 (98.0%) missing valuesMissing
college_university_gross has 978 (97.8%) missing valuesMissing
college_university_number has 986 (98.6%) missing valuesMissing
convention_center_gross_floor has 1000 (100.0%) missing valuesMissing
courthouse_gross_floor_area has 1000 (100.0%) missing valuesMissing
data_center_gross_floor_area has 994 (99.4%) missing valuesMissing
data_center_pdu_input_meter has 994 (99.4%) missing valuesMissing
data_center_pdu_output_meter has 994 (99.4%) missing valuesMissing
data_center_it_equipment has 994 (99.4%) missing valuesMissing
data_center_it_site_energy has 995 (99.5%) missing valuesMissing
data_center_it_source_energy has 995 (99.5%) missing valuesMissing
data_center_pue has 995 (99.5%) missing valuesMissing
data_center_national_median has 1000 (100.0%) missing valuesMissing
data_center_ups_output_meter has 994 (99.4%) missing valuesMissing
data_center_cooling_equipment has 998 (99.8%) missing valuesMissing
data_center_it_energy has 994 (99.4%) missing valuesMissing
data_center_ups_system has 998 (99.8%) missing valuesMissing
distribution_center_gross has 987 (98.7%) missing valuesMissing
enclosed_mall_gross_floor has 998 (99.8%) missing valuesMissing
energy_power_station_gross has 1000 (100.0%) missing valuesMissing
financial_office_gross_floor has 980 (98.0%) missing valuesMissing
financial_office_number_of has 980 (98.0%) missing valuesMissing
financial_office_number_of_1 has 980 (98.0%) missing valuesMissing
financial_office_weekly has 980 (98.0%) missing valuesMissing
fitness_center_health_club has 992 (99.2%) missing valuesMissing
food_sales_gross_floor_area has 994 (99.4%) missing valuesMissing
food_service_gross_floor has 997 (99.7%) missing valuesMissing
hospital_general_medical has 986 (98.6%) missing valuesMissing
hospital_general_medical_1 has 986 (98.6%) missing valuesMissing
hospital_general_medical_2 has 986 (98.6%) missing valuesMissing
hospital_general_medical_3 has 988 (98.8%) missing valuesMissing
hospital_general_medical_4 has 986 (98.6%) missing valuesMissing
hospital_general_medical_5 has 986 (98.6%) missing valuesMissing
hospital_general_medical_6 has 986 (98.6%) missing valuesMissing
hospital_general_medical_7 has 986 (98.6%) missing valuesMissing
hospital_general_medical_8 has 986 (98.6%) missing valuesMissing
hospital_general_medical_9 has 986 (98.6%) missing valuesMissing
hospital_general_medical_10 has 986 (98.6%) missing valuesMissing
hospital_general_medical_11 has 986 (98.6%) missing valuesMissing
hospital_general_medical_12 has 986 (98.6%) missing valuesMissing
medical_office_gross_floor has 976 (97.6%) missing valuesMissing
medical_office_number_of has 996 (99.6%) missing valuesMissing
medical_office_number_of_1 has 976 (97.6%) missing valuesMissing
medical_office_percent_that has 976 (97.6%) missing valuesMissing
medical_office_percent_that_1 has 976 (97.6%) missing valuesMissing
medical_office_weekly has 976 (97.6%) missing valuesMissing
outpatient_rehabilitation has 997 (99.7%) missing valuesMissing
urgent_care_clinic_other has 996 (99.6%) missing valuesMissing
k_12_school_gross_floor_area has 980 (98.0%) missing valuesMissing
laboratory_gross_floor_area has 996 (99.6%) missing valuesMissing
mailing_center_post_office has 999 (99.9%) missing valuesMissing
manufacturing_industrial has 979 (97.9%) missing valuesMissing
movie_theater_gross_floor has 999 (99.9%) missing valuesMissing
multifamily_housing_gross has 499 (49.9%) missing valuesMissing
multifamily_housing_government has 635 (63.5%) missing valuesMissing
multifamily_housing_number has 501 (50.1%) missing valuesMissing
multifamily_housing_number_1 has 657 (65.7%) missing valuesMissing
multifamily_housing_number_2 has 638 (63.8%) missing valuesMissing
multifamily_housing_total has 500 (50.0%) missing valuesMissing
multifamily_housing_percent has 573 (57.3%) missing valuesMissing
multifamily_housing_percent_1 has 560 (56.0%) missing valuesMissing
multifamily_housing_resident has 658 (65.8%) missing valuesMissing
multifamily_housing_number_3 has 501 (50.1%) missing valuesMissing
multifamily_housing_total_1 has 500 (50.0%) missing valuesMissing
multifamily_housing_number_4 has 500 (50.0%) missing valuesMissing
multifamily_housing_number_5 has 500 (50.0%) missing valuesMissing
multifamily_housing_number_6 has 501 (50.1%) missing valuesMissing
multifamily_housing_number_7 has 501 (50.1%) missing valuesMissing
other_computer_density_number has 945 (94.5%) missing valuesMissing
office_gross_floor_area_ft has 768 (76.8%) missing valuesMissing
office_number_of_computers has 768 (76.8%) missing valuesMissing
office_number_of_workers has 768 (76.8%) missing valuesMissing
office_percent_that_can_be has 768 (76.8%) missing valuesMissing
office_percent_that_can_be_1 has 768 (76.8%) missing valuesMissing
office_weekly_operating_hours has 768 (76.8%) missing valuesMissing
office_worker_density_number has 768 (76.8%) missing valuesMissing
museum_gross_floor_area_ft has 995 (99.5%) missing valuesMissing
non_refrigerated_warehouse has 963 (96.3%) missing valuesMissing
other_gross_floor_area_ft has 923 (92.3%) missing valuesMissing
other_weekly_operating_hours has 941 (94.1%) missing valuesMissing
other_number_of_computers has 942 (94.2%) missing valuesMissing
other_number_of_workers_on has 942 (94.2%) missing valuesMissing
performing_arts_gross_floor has 998 (99.8%) missing valuesMissing
pre_school_daycare_gross has 998 (99.8%) missing valuesMissing
supermarket_grocery_gross has 979 (97.9%) missing valuesMissing
refrigerated_warehouse_gross has 988 (98.8%) missing valuesMissing
repair_services_vehicle_shoe has 1000 (100.0%) missing valuesMissing
residence_hall_dormitory has 988 (98.8%) missing valuesMissing
restaurant_gross_floor_area has 964 (96.4%) missing valuesMissing
self_storage_facility_gross has 989 (98.9%) missing valuesMissing
senior_care_community_gross has 984 (98.4%) missing valuesMissing
social_meeting_hall_gross has 998 (99.8%) missing valuesMissing
wholesale_club_supercenter has 1000 (100.0%) missing valuesMissing
worship_facility_gross_floor has 994 (99.4%) missing valuesMissing
retail_store_gross_floor has 913 (91.3%) missing valuesMissing
restaurant_worker_density has 971 (97.1%) missing valuesMissing
restaurant_weekly_operating has 970 (97.0%) missing valuesMissing
retail_store_walk_in has 915 (91.5%) missing valuesMissing
retail_store_percent_that has 914 (91.4%) missing valuesMissing
retail_store_open_or_closed has 915 (91.5%) missing valuesMissing
retail_store_number_of_walk has 914 (91.4%) missing valuesMissing
retail_store_number_of_open has 914 (91.4%) missing valuesMissing
parking_gross_floor_area has 934 (93.4%) missing valuesMissing
parking_open_parking_lot has 934 (93.4%) missing valuesMissing
hotel_gross_floor_area_ft has 947 (94.7%) missing valuesMissing
hotel_gym_fitness_center has 969 (96.9%) missing valuesMissing
hotel_room_density_number has 947 (94.7%) missing valuesMissing
hotel_worker_density_number has 947 (94.7%) missing valuesMissing
hotel_percent_that_can_be has 947 (94.7%) missing valuesMissing
estimated_data_flag_1 has 995 (99.5%) missing valuesMissing
data_quality_checker_date has 528 (52.8%) missing valuesMissing
property_gfa_calculated_2 has 934 (93.4%) missing valuesMissing
water_current_date has 210 (21.0%) missing valuesMissing
water_use_all_water_sources has 360 (36.0%) missing valuesMissing
indoor_water_use_all_water has 414 (41.4%) missing valuesMissing
indoor_water_use_intensity has 414 (41.4%) missing valuesMissing
outdoor_water_use_all_water has 996 (99.6%) missing valuesMissing
municipally_supplied_potable has 939 (93.9%) missing valuesMissing
municipally_supplied_potable_1 has 414 (41.4%) missing valuesMissing
water_use_intensity_all_water has 360 (36.0%) missing valuesMissing
municipally_supplied_potable_2 has 996 (99.6%) missing valuesMissing
water_score_multifamily_only has 972 (97.2%) missing valuesMissing
irrigated_area_ft has 920 (92.0%) missing valuesMissing
third_party_certification has 996 (99.6%) missing valuesMissing
third_party_certification_1 has 996 (99.6%) missing valuesMissing
third_party_certification_2 has 996 (99.6%) missing valuesMissing
supermarket_grocery_open has 991 (99.1%) missing valuesMissing
convenience_store_with_gas has 1000 (100.0%) missing valuesMissing
convenience_store_with_gas_1 has 1000 (100.0%) missing valuesMissing
financial_office_computer has 982 (98.2%) missing valuesMissing
senior_care_community_living has 984 (98.4%) missing valuesMissing
last_modified_date_property has 51 (5.1%) missing valuesMissing
last_modified_date_electric has 126 (12.6%) missing valuesMissing
last_modified_date_gas_meters has 237 (23.7%) missing valuesMissing
last_modified_date_non has 632 (63.2%) missing valuesMissing
last_modified_date_water has 320 (32.0%) missing valuesMissing
borough has 58 (5.8%) missing valuesMissing
latitude has 58 (5.8%) missing valuesMissing
longitude has 58 (5.8%) missing valuesMissing
community_board has 58 (5.8%) missing valuesMissing
council_district has 58 (5.8%) missing valuesMissing
census_tract has 58 (5.8%) missing valuesMissing
nta has 58 (5.8%) missing valuesMissing
0 has unique valuesUnique
fuel_oil_1_use_kbtu is an unsupported type, check if it needs cleaning or further analysisUnsupported
kerosene_use_kbtu is an unsupported type, check if it needs cleaning or further analysisUnsupported
propane_use_kbtu is an unsupported type, check if it needs cleaning or further analysisUnsupported
district_hot_water_use_kbtu is an unsupported type, check if it needs cleaning or further analysisUnsupported
costar_property_id is an unsupported type, check if it needs cleaning or further analysisUnsupported
automobile_dealership_gross is an unsupported type, check if it needs cleaning or further analysisUnsupported
convention_center_gross_floor is an unsupported type, check if it needs cleaning or further analysisUnsupported
courthouse_gross_floor_area is an unsupported type, check if it needs cleaning or further analysisUnsupported
data_center_national_median is an unsupported type, check if it needs cleaning or further analysisUnsupported
energy_power_station_gross is an unsupported type, check if it needs cleaning or further analysisUnsupported
repair_services_vehicle_shoe is an unsupported type, check if it needs cleaning or further analysisUnsupported
wholesale_club_supercenter is an unsupported type, check if it needs cleaning or further analysisUnsupported
convenience_store_with_gas is an unsupported type, check if it needs cleaning or further analysisUnsupported
convenience_store_with_gas_1 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-09 23:27:32.786998
Analysis finished2023-12-09 23:27:41.341609
Duration8.55 seconds
Software versionydata-profiling v0.0.dev0
Download configurationconfig.json

Variables

0
Real number (ℝ)

UNIQUE 

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean500.5
Minimum1
Maximum1000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2023-12-09T23:27:41.914082image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile50.95
Q1250.75
median500.5
Q3750.25
95-th percentile950.05
Maximum1000
Range999
Interquartile range (IQR)499.5

Descriptive statistics

Standard deviation288.8194361
Coefficient of variation (CV)0.5770618104
Kurtosis-1.2
Mean500.5
Median Absolute Deviation (MAD)250
Skewness0
Sum500500
Variance83416.66667
MonotonicityStrictly increasing
2023-12-09T23:27:42.079628image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
672 1
 
0.1%
659 1
 
0.1%
660 1
 
0.1%
661 1
 
0.1%
662 1
 
0.1%
663 1
 
0.1%
664 1
 
0.1%
665 1
 
0.1%
666 1
 
0.1%
Other values (990) 990
99.0%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
ValueCountFrequency (%)
1000 1
0.1%
999 1
0.1%
998 1
0.1%
997 1
0.1%
996 1
0.1%
Distinct890
Distinct (%)89.0%
Missing0
Missing (%)0.0%
Memory size62.6 KiB
2023-12-09T23:27:42.715096image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters7000
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique797 ?
Unique (%)79.7%

Sample

1st row4593574
2nd row6224375
3rd row2967701
4th row4898531
5th row2917939
ValueCountFrequency (%)
3772862 5
 
0.5%
6213321 5
 
0.5%
3113637 4
 
0.4%
6153751 3
 
0.3%
4409966 3
 
0.3%
4960043 3
 
0.3%
2689677 3
 
0.3%
4391198 3
 
0.3%
2817671 3
 
0.3%
2936772 3
 
0.3%
Other values (880) 965
96.5%
2023-12-09T23:27:43.495144image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 1147
16.4%
6 871
12.4%
3 714
10.2%
4 707
10.1%
7 670
9.6%
1 627
9.0%
8 587
8.4%
5 566
8.1%
0 563
8.0%
9 548
7.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1147
16.4%
6 871
12.4%
3 714
10.2%
4 707
10.1%
7 670
9.6%
1 627
9.0%
8 587
8.4%
5 566
8.1%
0 563
8.0%
9 548
7.8%

Most occurring scripts

ValueCountFrequency (%)
Common 7000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 1147
16.4%
6 871
12.4%
3 714
10.2%
4 707
10.1%
7 670
9.6%
1 627
9.0%
8 587
8.4%
5 566
8.1%
0 563
8.0%
9 548
7.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 1147
16.4%
6 871
12.4%
3 714
10.2%
4 707
10.1%
7 670
9.6%
1 627
9.0%
8 587
8.4%
5 566
8.1%
0 563
8.0%
9 548
7.8%

year_ending
Text

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size78.2 KiB
2023-12-09T23:27:43.697979image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length23
Median length23
Mean length23
Min length23

Characters and Unicode

Total characters23000
Distinct characters9
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2017-12-31T00:00:00.000
2nd row2017-12-31T00:00:00.000
3rd row2017-12-31T00:00:00.000
4th row2017-12-31T00:00:00.000
5th row2017-12-31T00:00:00.000
ValueCountFrequency (%)
2017-12-31t00:00:00.000 1000
100.0%
2023-12-09T23:27:43.995411image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10000
43.5%
1 3000
 
13.0%
2 2000
 
8.7%
- 2000
 
8.7%
: 2000
 
8.7%
7 1000
 
4.3%
3 1000
 
4.3%
T 1000
 
4.3%
. 1000
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17000
73.9%
Other Punctuation 3000
 
13.0%
Dash Punctuation 2000
 
8.7%
Uppercase Letter 1000
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10000
58.8%
1 3000
 
17.6%
2 2000
 
11.8%
7 1000
 
5.9%
3 1000
 
5.9%
Other Punctuation
ValueCountFrequency (%)
: 2000
66.7%
. 1000
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 2000
100.0%
Uppercase Letter
ValueCountFrequency (%)
T 1000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 22000
95.7%
Latin 1000
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10000
45.5%
1 3000
 
13.6%
2 2000
 
9.1%
- 2000
 
9.1%
: 2000
 
9.1%
7 1000
 
4.5%
3 1000
 
4.5%
. 1000
 
4.5%
Latin
ValueCountFrequency (%)
T 1000
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10000
43.5%
1 3000
 
13.0%
2 2000
 
8.7%
- 2000
 
8.7%
: 2000
 
8.7%
7 1000
 
4.3%
3 1000
 
4.3%
T 1000
 
4.3%
. 1000
 
4.3%
Distinct56
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size78.2 KiB
2023-12-09T23:27:44.292628image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length23
Median length23
Mean length23
Min length23

Characters and Unicode

Total characters23000
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)1.0%

Sample

1st row2018-02-14T00:00:00.000
2nd row2018-02-14T00:00:00.000
3rd row2018-02-14T00:00:00.000
4th row2018-02-14T00:00:00.000
5th row2018-02-14T00:00:00.000
ValueCountFrequency (%)
2018-04-03t00:00:00.000 98
 
9.8%
2018-04-04t00:00:00.000 93
 
9.3%
2018-03-29t00:00:00.000 87
 
8.7%
2018-04-02t00:00:00.000 60
 
6.0%
2018-03-20t00:00:00.000 53
 
5.3%
2018-03-28t00:00:00.000 48
 
4.8%
2018-03-26t00:00:00.000 48
 
4.8%
2018-03-27t00:00:00.000 40
 
4.0%
2018-03-30t00:00:00.000 34
 
3.4%
2018-03-12t00:00:00.000 33
 
3.3%
Other values (46) 406
40.6%
2023-12-09T23:27:44.731482image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11464
49.8%
- 2000
 
8.7%
: 2000
 
8.7%
2 1654
 
7.2%
1 1233
 
5.4%
8 1069
 
4.6%
T 1000
 
4.3%
. 1000
 
4.3%
3 811
 
3.5%
4 410
 
1.8%
Other values (4) 359
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17000
73.9%
Other Punctuation 3000
 
13.0%
Dash Punctuation 2000
 
8.7%
Uppercase Letter 1000
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11464
67.4%
2 1654
 
9.7%
1 1233
 
7.3%
8 1069
 
6.3%
3 811
 
4.8%
4 410
 
2.4%
9 142
 
0.8%
6 98
 
0.6%
5 63
 
0.4%
7 56
 
0.3%
Other Punctuation
ValueCountFrequency (%)
: 2000
66.7%
. 1000
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 2000
100.0%
Uppercase Letter
ValueCountFrequency (%)
T 1000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 22000
95.7%
Latin 1000
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11464
52.1%
- 2000
 
9.1%
: 2000
 
9.1%
2 1654
 
7.5%
1 1233
 
5.6%
8 1069
 
4.9%
. 1000
 
4.5%
3 811
 
3.7%
4 410
 
1.9%
9 142
 
0.6%
Other values (3) 217
 
1.0%
Latin
ValueCountFrequency (%)
T 1000
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11464
49.8%
- 2000
 
8.7%
: 2000
 
8.7%
2 1654
 
7.2%
1 1233
 
5.4%
8 1069
 
4.6%
T 1000
 
4.3%
. 1000
 
4.3%
3 811
 
3.5%
4 410
 
1.8%
Other values (4) 359
 
1.6%
Distinct249
Distinct (%)24.9%
Missing0
Missing (%)0.0%
Memory size60.8 KiB
2023-12-09T23:27:45.048506image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.107
Min length3

Characters and Unicode

Total characters5107
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique130 ?
Unique (%)13.0%

Sample

1st row129858
2nd row74175
3rd row8760
4th row8760
5th row12272
ValueCountFrequency (%)
31047 60
 
6.0%
46448 58
 
5.8%
19173 49
 
4.9%
41987 43
 
4.3%
11575 38
 
3.8%
58761 36
 
3.6%
15870 22
 
2.2%
115010 20
 
2.0%
53293 19
 
1.9%
35108 17
 
1.7%
Other values (239) 638
63.8%
2023-12-09T23:27:45.481048image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 837
16.4%
4 588
11.5%
7 539
10.6%
5 507
9.9%
0 502
9.8%
3 474
9.3%
8 463
9.1%
6 413
8.1%
2 407
8.0%
9 377
7.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5107
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 837
16.4%
4 588
11.5%
7 539
10.6%
5 507
9.9%
0 502
9.8%
3 474
9.3%
8 463
9.1%
6 413
8.1%
2 407
8.0%
9 377
7.4%

Most occurring scripts

ValueCountFrequency (%)
Common 5107
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 837
16.4%
4 588
11.5%
7 539
10.6%
5 507
9.9%
0 502
9.8%
3 474
9.3%
8 463
9.1%
6 413
8.1%
2 407
8.0%
9 377
7.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5107
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 837
16.4%
4 588
11.5%
7 539
10.6%
5 507
9.9%
0 502
9.8%
3 474
9.3%
8 463
9.1%
6 413
8.1%
2 407
8.0%
9 377
7.4%
Distinct890
Distinct (%)89.0%
Missing0
Missing (%)0.0%
Memory size62.6 KiB
2023-12-09T23:27:45.845980image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters7000
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique797 ?
Unique (%)79.7%

Sample

1st row4593574
2nd row6224375
3rd row2967701
4th row4898531
5th row2917939
ValueCountFrequency (%)
3772862 5
 
0.5%
6213321 5
 
0.5%
3113637 4
 
0.4%
6153751 3
 
0.3%
4409966 3
 
0.3%
4960043 3
 
0.3%
2689677 3
 
0.3%
4391198 3
 
0.3%
2817671 3
 
0.3%
2936772 3
 
0.3%
Other values (880) 965
96.5%
2023-12-09T23:27:46.337311image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 1147
16.4%
6 871
12.4%
3 714
10.2%
4 707
10.1%
7 670
9.6%
1 627
9.0%
8 587
8.4%
5 566
8.1%
0 563
8.0%
9 548
7.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1147
16.4%
6 871
12.4%
3 714
10.2%
4 707
10.1%
7 670
9.6%
1 627
9.0%
8 587
8.4%
5 566
8.1%
0 563
8.0%
9 548
7.8%

Most occurring scripts

ValueCountFrequency (%)
Common 7000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 1147
16.4%
6 871
12.4%
3 714
10.2%
4 707
10.1%
7 670
9.6%
1 627
9.0%
8 587
8.4%
5 566
8.1%
0 563
8.0%
9 548
7.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 1147
16.4%
6 871
12.4%
3 714
10.2%
4 707
10.1%
7 670
9.6%
1 627
9.0%
8 587
8.4%
5 566
8.1%
0 563
8.0%
9 548
7.8%
Distinct890
Distinct (%)89.0%
Missing0
Missing (%)0.0%
Memory size76.4 KiB
2023-12-09T23:27:46.768019image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length80
Median length43
Mean length21.1
Min length2

Characters and Unicode

Total characters21100
Distinct characters75
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique797 ?
Unique (%)79.7%

Sample

1st rowThe Argonaut Building
2nd rowOperative Cakes
3rd rowCathedral Preparatory Seminary
4th rowThe Nomad Hotel
5th row10 West 27 Street Corp
ValueCountFrequency (%)
234
 
6.2%
street 140
 
3.7%
avenue 121
 
3.2%
llc 121
 
3.2%
ave 85
 
2.2%
west 79
 
2.1%
realty 67
 
1.8%
st 55
 
1.4%
east 55
 
1.4%
corp 40
 
1.1%
Other values (1424) 2801
73.7%
2023-12-09T23:27:47.400158image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2808
 
13.3%
e 1801
 
8.5%
t 1135
 
5.4%
r 967
 
4.6%
a 924
 
4.4%
n 868
 
4.1%
o 819
 
3.9%
s 675
 
3.2%
i 579
 
2.7%
l 573
 
2.7%
Other values (65) 9951
47.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 11223
53.2%
Uppercase Letter 3601
 
17.1%
Decimal Number 2901
 
13.7%
Space Separator 2808
 
13.3%
Dash Punctuation 357
 
1.7%
Other Punctuation 183
 
0.9%
Connector Punctuation 8
 
< 0.1%
Close Punctuation 7
 
< 0.1%
Open Punctuation 7
 
< 0.1%
Math Symbol 5
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1801
16.0%
t 1135
10.1%
r 967
 
8.6%
a 924
 
8.2%
n 868
 
7.7%
o 819
 
7.3%
s 675
 
6.0%
i 579
 
5.2%
l 573
 
5.1%
d 361
 
3.2%
Other values (16) 2521
22.5%
Uppercase Letter
ValueCountFrequency (%)
C 392
 
10.9%
S 385
 
10.7%
A 343
 
9.5%
L 328
 
9.1%
E 227
 
6.3%
R 192
 
5.3%
T 186
 
5.2%
H 174
 
4.8%
M 167
 
4.6%
B 166
 
4.6%
Other values (16) 1041
28.9%
Decimal Number
ValueCountFrequency (%)
1 532
18.3%
0 368
12.7%
2 342
11.8%
3 327
11.3%
5 318
11.0%
4 282
9.7%
8 203
 
7.0%
7 202
 
7.0%
6 167
 
5.8%
9 160
 
5.5%
Other Punctuation
ValueCountFrequency (%)
. 93
50.8%
, 42
23.0%
& 23
 
12.6%
/ 17
 
9.3%
: 3
 
1.6%
' 3
 
1.6%
* 2
 
1.1%
Space Separator
ValueCountFrequency (%)
2808
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 357
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Math Symbol
ValueCountFrequency (%)
+ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 14824
70.3%
Common 6276
29.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1801
 
12.1%
t 1135
 
7.7%
r 967
 
6.5%
a 924
 
6.2%
n 868
 
5.9%
o 819
 
5.5%
s 675
 
4.6%
i 579
 
3.9%
l 573
 
3.9%
C 392
 
2.6%
Other values (42) 6091
41.1%
Common
ValueCountFrequency (%)
2808
44.7%
1 532
 
8.5%
0 368
 
5.9%
- 357
 
5.7%
2 342
 
5.4%
3 327
 
5.2%
5 318
 
5.1%
4 282
 
4.5%
8 203
 
3.2%
7 202
 
3.2%
Other values (13) 537
 
8.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21100
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2808
 
13.3%
e 1801
 
8.5%
t 1135
 
5.4%
r 967
 
4.6%
a 924
 
4.4%
n 868
 
4.1%
o 819
 
3.9%
s 675
 
3.2%
i 579
 
2.7%
l 573
 
2.7%
Other values (65) 9951
47.2%

parent_property_id
Text

MISSING 

Distinct14
Distinct (%)38.9%
Missing964
Missing (%)96.4%
Memory size32.5 KiB
2023-12-09T23:27:47.607240image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length14
Median length7
Mean length7.777777778
Min length7

Characters and Unicode

Total characters280
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)16.7%

Sample

1st row62242466224246
2nd row62242466224246
3rd row6224246
4th row6128948
5th row6128948
ValueCountFrequency (%)
5846549 7
19.4%
3615313 5
13.9%
6227961 5
13.9%
6264462 3
8.3%
4926122 3
8.3%
6128948 3
8.3%
58585425858542 2
 
5.6%
62242466224246 2
 
5.6%
3612678 1
 
2.8%
5858542 1
 
2.8%
Other values (4) 4
11.1%
2023-12-09T23:27:47.947576image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 55
19.6%
2 49
17.5%
4 43
15.4%
5 35
12.5%
8 26
9.3%
1 25
8.9%
9 20
 
7.1%
3 20
 
7.1%
7 6
 
2.1%
0 1
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 280
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 55
19.6%
2 49
17.5%
4 43
15.4%
5 35
12.5%
8 26
9.3%
1 25
8.9%
9 20
 
7.1%
3 20
 
7.1%
7 6
 
2.1%
0 1
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
Common 280
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 55
19.6%
2 49
17.5%
4 43
15.4%
5 35
12.5%
8 26
9.3%
1 25
8.9%
9 20
 
7.1%
3 20
 
7.1%
7 6
 
2.1%
0 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 280
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 55
19.6%
2 49
17.5%
4 43
15.4%
5 35
12.5%
8 26
9.3%
1 25
8.9%
9 20
 
7.1%
3 20
 
7.1%
7 6
 
2.1%
0 1
 
0.4%

parent_property_name
Text

MISSING 

Distinct14
Distinct (%)38.9%
Missing964
Missing (%)96.4%
Memory size33.0 KiB
2023-12-09T23:27:48.193896image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length40
Median length25
Mean length21.52777778
Min length6

Characters and Unicode

Total characters775
Distinct characters54
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)16.7%

Sample

1st row955/989, 955/989
2nd row955/989, 955/989
3rd row955/989
4th rowHoward
5th rowHoward
ValueCountFrequency (%)
campus 8
 
5.8%
west 7
 
5.1%
square 7
 
5.1%
farms 7
 
5.1%
7
 
5.1%
cancer 5
 
3.6%
zysman 5
 
3.6%
gottesman 5
 
3.6%
955/989 5
 
3.6%
1 5
 
3.6%
Other values (27) 76
55.5%
2023-12-09T23:27:48.577718image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
101
 
13.0%
e 64
 
8.3%
a 56
 
7.2%
r 42
 
5.4%
n 38
 
4.9%
m 37
 
4.8%
t 36
 
4.6%
s 35
 
4.5%
o 29
 
3.7%
C 29
 
3.7%
Other values (44) 308
39.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 458
59.1%
Uppercase Letter 114
 
14.7%
Space Separator 101
 
13.0%
Decimal Number 81
 
10.5%
Other Punctuation 16
 
2.1%
Dash Punctuation 3
 
0.4%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 64
14.0%
a 56
12.2%
r 42
9.2%
n 38
8.3%
m 37
8.1%
t 36
7.9%
s 35
7.6%
o 29
 
6.3%
u 20
 
4.4%
i 18
 
3.9%
Other values (13) 83
18.1%
Uppercase Letter
ValueCountFrequency (%)
C 29
25.4%
S 16
14.0%
L 13
11.4%
K 10
 
8.8%
M 8
 
7.0%
H 8
 
7.0%
B 8
 
7.0%
W 7
 
6.1%
F 7
 
6.1%
A 3
 
2.6%
Other values (4) 5
 
4.4%
Decimal Number
ValueCountFrequency (%)
1 23
28.4%
9 15
18.5%
8 14
17.3%
5 11
13.6%
0 10
12.3%
2 5
 
6.2%
6 1
 
1.2%
4 1
 
1.2%
7 1
 
1.2%
Other Punctuation
ValueCountFrequency (%)
/ 5
31.2%
, 4
25.0%
& 4
25.0%
. 3
18.8%
Space Separator
ValueCountFrequency (%)
101
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 572
73.8%
Common 203
 
26.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 64
 
11.2%
a 56
 
9.8%
r 42
 
7.3%
n 38
 
6.6%
m 37
 
6.5%
t 36
 
6.3%
s 35
 
6.1%
o 29
 
5.1%
C 29
 
5.1%
u 20
 
3.5%
Other values (27) 186
32.5%
Common
ValueCountFrequency (%)
101
49.8%
1 23
 
11.3%
9 15
 
7.4%
8 14
 
6.9%
5 11
 
5.4%
0 10
 
4.9%
2 5
 
2.5%
/ 5
 
2.5%
, 4
 
2.0%
& 4
 
2.0%
Other values (7) 11
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 775
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
101
 
13.0%
e 64
 
8.3%
a 56
 
7.2%
r 42
 
5.4%
n 38
 
4.9%
m 37
 
4.8%
t 36
 
4.6%
s 35
 
4.5%
o 29
 
3.7%
C 29
 
3.7%
Other values (44) 308
39.7%
Distinct864
Distinct (%)89.3%
Missing32
Missing (%)3.2%
Memory size66.0 KiB
2023-12-09T23:27:48.886529image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length82
Median length12
Mean length11.62603306
Min length6

Characters and Unicode

Total characters11254
Distinct characters28
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique790 ?
Unique (%)81.6%

Sample

1st row1010287502
2nd row2-00560-0062;2-05560-0062
3rd row4-01872-0007
4th row1-00829-0050
5th row1-00828-0053
ValueCountFrequency (%)
2039447501 15
 
1.5%
4-04382-001 5
 
0.5%
1014860001 5
 
0.5%
manhattan 5
 
0.5%
block 4
 
0.4%
lot 4
 
0.4%
4026100118 4
 
0.4%
4026020170 3
 
0.3%
1-01276-0042 3
 
0.3%
1-00832-0049 3
 
0.3%
Other values (870) 944
94.9%
2023-12-09T23:27:49.352731image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3688
32.8%
1 1482
13.2%
- 1323
 
11.8%
2 913
 
8.1%
3 715
 
6.4%
4 677
 
6.0%
5 604
 
5.4%
8 480
 
4.3%
6 453
 
4.0%
7 447
 
4.0%
Other values (18) 472
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9768
86.8%
Dash Punctuation 1323
 
11.8%
Lowercase Letter 66
 
0.6%
Other Punctuation 56
 
0.5%
Space Separator 27
 
0.2%
Uppercase Letter 14
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3688
37.8%
1 1482
15.2%
2 913
 
9.3%
3 715
 
7.3%
4 677
 
6.9%
5 604
 
6.2%
8 480
 
4.9%
6 453
 
4.6%
7 447
 
4.6%
9 309
 
3.2%
Lowercase Letter
ValueCountFrequency (%)
a 16
24.2%
t 14
21.2%
n 11
16.7%
o 8
12.1%
h 5
 
7.6%
l 4
 
6.1%
c 4
 
6.1%
k 4
 
6.1%
Other Punctuation
ValueCountFrequency (%)
/ 23
41.1%
; 18
32.1%
, 12
21.4%
: 2
 
3.6%
. 1
 
1.8%
Uppercase Letter
ValueCountFrequency (%)
M 6
42.9%
B 4
28.6%
L 4
28.6%
Dash Punctuation
ValueCountFrequency (%)
- 1323
100.0%
Space Separator
ValueCountFrequency (%)
27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11174
99.3%
Latin 80
 
0.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3688
33.0%
1 1482
13.3%
- 1323
 
11.8%
2 913
 
8.2%
3 715
 
6.4%
4 677
 
6.1%
5 604
 
5.4%
8 480
 
4.3%
6 453
 
4.1%
7 447
 
4.0%
Other values (7) 392
 
3.5%
Latin
ValueCountFrequency (%)
a 16
20.0%
t 14
17.5%
n 11
13.8%
o 8
10.0%
M 6
 
7.5%
h 5
 
6.2%
B 4
 
5.0%
l 4
 
5.0%
c 4
 
5.0%
k 4
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11254
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3688
32.8%
1 1482
13.2%
- 1323
 
11.8%
2 913
 
8.1%
3 715
 
6.4%
4 677
 
6.0%
5 604
 
5.4%
8 480
 
4.3%
6 453
 
4.0%
7 447
 
4.0%
Other values (18) 472
 
4.2%
Distinct840
Distinct (%)90.2%
Missing69
Missing (%)6.9%
Memory size63.1 KiB
2023-12-09T23:27:49.596013image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length415
Median length7
Mean length9.912996778
Min length1

Characters and Unicode

Total characters9229
Distinct characters14
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique763 ?
Unique (%)82.0%

Sample

1st row1024898
2nd row2087721;2080293
3rd row4046340
4th row1080710
5th row1015657
ValueCountFrequency (%)
4860641 5
 
0.5%
4058991 4
 
0.4%
1035326 3
 
0.3%
1015792 3
 
0.3%
3124302 3
 
0.3%
4058970 3
 
0.3%
3183160 3
 
0.3%
2015299 3
 
0.3%
1035356 3
 
0.3%
1032045 3
 
0.3%
Other values (832) 900
96.5%
2023-12-09T23:27:49.968846image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1507
16.3%
4 1255
13.6%
1 1252
13.6%
2 882
9.6%
3 841
9.1%
5 787
8.5%
8 649
7.0%
7 577
 
6.3%
6 568
 
6.2%
9 566
 
6.1%
Other values (4) 345
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8884
96.3%
Other Punctuation 339
 
3.7%
Dash Punctuation 4
 
< 0.1%
Space Separator 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1507
17.0%
4 1255
14.1%
1 1252
14.1%
2 882
9.9%
3 841
9.5%
5 787
8.9%
8 649
7.3%
7 577
 
6.5%
6 568
 
6.4%
9 566
 
6.4%
Other Punctuation
ValueCountFrequency (%)
; 337
99.4%
: 2
 
0.6%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9229
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1507
16.3%
4 1255
13.6%
1 1252
13.6%
2 882
9.6%
3 841
9.1%
5 787
8.5%
8 649
7.0%
7 577
 
6.3%
6 568
 
6.2%
9 566
 
6.1%
Other values (4) 345
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9229
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1507
16.3%
4 1255
13.6%
1 1252
13.6%
2 882
9.6%
3 841
9.1%
5 787
8.5%
8 649
7.0%
7 577
 
6.3%
6 568
 
6.2%
9 566
 
6.1%
Other values (4) 345
 
3.7%
Distinct878
Distinct (%)87.8%
Missing0
Missing (%)0.0%
Memory size73.2 KiB
2023-12-09T23:27:50.442101image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length44
Median length28
Mean length17.833
Min length5

Characters and Unicode

Total characters17833
Distinct characters67
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique777 ?
Unique (%)77.7%

Sample

1st row224 West 57th St
2nd row711-733 Brush Avenue
3rd row56-25 92nd Street
4th row1170 Broadway
5th row1155 Broadway
ValueCountFrequency (%)
street 342
 
10.3%
avenue 253
 
7.6%
west 133
 
4.0%
ave 130
 
3.9%
east 110
 
3.3%
st 82
 
2.5%
e 30
 
0.9%
broadway 27
 
0.8%
park 25
 
0.8%
blvd 24
 
0.7%
Other values (1108) 2166
65.2%
2023-12-09T23:27:51.074377image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2335
 
13.1%
e 1798
 
10.1%
t 1459
 
8.2%
1 829
 
4.6%
r 767
 
4.3%
n 649
 
3.6%
a 571
 
3.2%
0 560
 
3.1%
2 552
 
3.1%
5 509
 
2.9%
Other values (57) 7804
43.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8706
48.8%
Decimal Number 4271
23.9%
Space Separator 2335
 
13.1%
Uppercase Letter 2214
 
12.4%
Dash Punctuation 199
 
1.1%
Other Punctuation 104
 
0.6%
Open Punctuation 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1798
20.7%
t 1459
16.8%
r 767
8.8%
n 649
 
7.5%
a 571
 
6.6%
s 475
 
5.5%
v 437
 
5.0%
o 384
 
4.4%
u 360
 
4.1%
h 351
 
4.0%
Other values (15) 1455
16.7%
Uppercase Letter
ValueCountFrequency (%)
S 474
21.4%
A 413
18.7%
E 255
11.5%
W 185
 
8.4%
B 131
 
5.9%
T 125
 
5.6%
P 91
 
4.1%
M 71
 
3.2%
C 70
 
3.2%
R 68
 
3.1%
Other values (14) 331
15.0%
Decimal Number
ValueCountFrequency (%)
1 829
19.4%
0 560
13.1%
2 552
12.9%
5 509
11.9%
3 433
10.1%
4 371
8.7%
7 280
 
6.6%
8 262
 
6.1%
6 260
 
6.1%
9 215
 
5.0%
Other Punctuation
ValueCountFrequency (%)
. 89
85.6%
/ 9
 
8.7%
& 3
 
2.9%
, 3
 
2.9%
Space Separator
ValueCountFrequency (%)
2335
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 199
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10920
61.2%
Common 6913
38.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1798
16.5%
t 1459
13.4%
r 767
 
7.0%
n 649
 
5.9%
a 571
 
5.2%
s 475
 
4.3%
S 474
 
4.3%
v 437
 
4.0%
A 413
 
3.8%
o 384
 
3.5%
Other values (39) 3493
32.0%
Common
ValueCountFrequency (%)
2335
33.8%
1 829
 
12.0%
0 560
 
8.1%
2 552
 
8.0%
5 509
 
7.4%
3 433
 
6.3%
4 371
 
5.4%
7 280
 
4.1%
8 262
 
3.8%
6 260
 
3.8%
Other values (8) 522
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17833
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2335
 
13.1%
e 1798
 
10.1%
t 1459
 
8.2%
1 829
 
4.6%
r 767
 
4.3%
n 649
 
3.6%
a 571
 
3.2%
0 560
 
3.1%
2 552
 
3.1%
5 509
 
2.9%
Other values (57) 7804
43.8%

address_2
Text

MISSING 

Distinct15
Distinct (%)88.2%
Missing983
Missing (%)98.3%
Memory size32.1 KiB
2023-12-09T23:27:51.302095image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length27
Median length22
Mean length17.94117647
Min length6

Characters and Unicode

Total characters305
Distinct characters40
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)76.5%

Sample

1st rowPier 7
2nd row2011-01-05T00:00:00.000
3rd row2011-01-05T00:00:00.000
4th rowaka 1 MetroTech Center
5th row130 East 59th Street
ValueCountFrequency (%)
street 8
 
15.7%
east 4
 
7.8%
blvd 3
 
5.9%
2011-01-05t00:00:00.000 2
 
3.9%
francis 2
 
3.9%
lewis 2
 
3.9%
2583 2
 
3.9%
aka 2
 
3.9%
1505 1
 
2.0%
13-04 1
 
2.0%
Other values (24) 24
47.1%
2023-12-09T23:27:51.642967image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
34
 
11.1%
t 32
 
10.5%
0 30
 
9.8%
e 27
 
8.9%
r 15
 
4.9%
1 14
 
4.6%
5 13
 
4.3%
a 11
 
3.6%
S 9
 
3.0%
s 9
 
3.0%
Other values (30) 111
36.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 132
43.3%
Decimal Number 94
30.8%
Space Separator 34
 
11.1%
Uppercase Letter 29
 
9.5%
Dash Punctuation 8
 
2.6%
Other Punctuation 8
 
2.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 32
24.2%
e 27
20.5%
r 15
11.4%
a 11
 
8.3%
s 9
 
6.8%
h 8
 
6.1%
i 6
 
4.5%
l 5
 
3.8%
d 4
 
3.0%
n 3
 
2.3%
Other values (6) 12
 
9.1%
Decimal Number
ValueCountFrequency (%)
0 30
31.9%
1 14
14.9%
5 13
13.8%
3 9
 
9.6%
9 6
 
6.4%
7 5
 
5.3%
2 5
 
5.3%
6 4
 
4.3%
8 4
 
4.3%
4 4
 
4.3%
Uppercase Letter
ValueCountFrequency (%)
S 9
31.0%
B 4
13.8%
E 4
13.8%
T 3
 
10.3%
W 2
 
6.9%
L 2
 
6.9%
F 2
 
6.9%
P 1
 
3.4%
M 1
 
3.4%
C 1
 
3.4%
Other Punctuation
ValueCountFrequency (%)
. 4
50.0%
: 4
50.0%
Space Separator
ValueCountFrequency (%)
34
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 161
52.8%
Common 144
47.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 32
19.9%
e 27
16.8%
r 15
9.3%
a 11
 
6.8%
S 9
 
5.6%
s 9
 
5.6%
h 8
 
5.0%
i 6
 
3.7%
l 5
 
3.1%
B 4
 
2.5%
Other values (16) 35
21.7%
Common
ValueCountFrequency (%)
34
23.6%
0 30
20.8%
1 14
9.7%
5 13
 
9.0%
3 9
 
6.2%
- 8
 
5.6%
9 6
 
4.2%
7 5
 
3.5%
2 5
 
3.5%
6 4
 
2.8%
Other values (4) 16
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 305
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
34
 
11.1%
t 32
 
10.5%
0 30
 
9.8%
e 27
 
8.9%
r 15
 
4.9%
1 14
 
4.6%
5 13
 
4.3%
a 11
 
3.6%
S 9
 
3.0%
s 9
 
3.0%
Other values (30) 111
36.4%

city
Text

Distinct50
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size63.2 KiB
2023-12-09T23:27:51.851966image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length17
Median length8
Mean length7.614
Min length2

Characters and Unicode

Total characters7614
Distinct characters50
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)2.0%

Sample

1st rowNew York
2nd rowBronx
3rd rowFlushing
4th rowNew York
5th rowNew York
ValueCountFrequency (%)
new 441
29.1%
york 437
28.8%
bronx 200
13.2%
brooklyn 156
 
10.3%
queens 51
 
3.4%
manhattan 30
 
2.0%
island 30
 
2.0%
flushing 29
 
1.9%
city 28
 
1.8%
long 20
 
1.3%
Other values (31) 96
 
6.3%
2023-12-09T23:27:52.194836image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 959
12.6%
r 783
 
10.3%
n 580
 
7.6%
k 571
 
7.5%
e 568
 
7.5%
518
 
6.8%
N 440
 
5.8%
Y 432
 
5.7%
w 415
 
5.5%
B 341
 
4.5%
Other values (40) 2007
26.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5418
71.2%
Uppercase Letter 1673
 
22.0%
Space Separator 518
 
6.8%
Decimal Number 5
 
0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 440
26.3%
Y 432
25.8%
B 341
20.4%
Q 50
 
3.0%
O 45
 
2.7%
M 45
 
2.7%
R 40
 
2.4%
E 34
 
2.0%
K 34
 
2.0%
F 33
 
2.0%
Other values (14) 179
10.7%
Lowercase Letter
ValueCountFrequency (%)
o 959
17.7%
r 783
14.5%
n 580
10.7%
k 571
10.5%
e 568
10.5%
w 415
7.7%
l 228
 
4.2%
a 202
 
3.7%
x 200
 
3.7%
y 199
 
3.7%
Other values (12) 713
13.2%
Decimal Number
ValueCountFrequency (%)
1 2
40.0%
2 2
40.0%
3 1
20.0%
Space Separator
ValueCountFrequency (%)
518
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 7091
93.1%
Common 523
 
6.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 959
13.5%
r 783
11.0%
n 580
 
8.2%
k 571
 
8.1%
e 568
 
8.0%
N 440
 
6.2%
Y 432
 
6.1%
w 415
 
5.9%
B 341
 
4.8%
l 228
 
3.2%
Other values (36) 1774
25.0%
Common
ValueCountFrequency (%)
518
99.0%
1 2
 
0.4%
2 2
 
0.4%
3 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7614
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 959
12.6%
r 783
 
10.3%
n 580
 
7.6%
k 571
 
7.5%
e 568
 
7.5%
518
 
6.8%
N 440
 
5.8%
Y 432
 
5.7%
w 415
 
5.5%
B 341
 
4.5%
Other values (40) 2007
26.4%

county
Text

MISSING 

Distinct16
Distinct (%)11.2%
Missing857
Missing (%)85.7%
Memory size35.7 KiB
2023-12-09T23:27:52.635461image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length24
Median length13
Mean length5.881118881
Min length3

Characters and Unicode

Total characters841
Distinct characters36
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)2.8%

Sample

1st rowUnited States
2nd rowNew York
3rd rowUnited States of America
4th rowRichmond
5th rowUnited States
ValueCountFrequency (%)
usa 43
24.4%
kings 30
17.0%
new 23
13.1%
york 23
13.1%
queens 15
 
8.5%
manhattan 11
 
6.2%
bronx 10
 
5.7%
united 8
 
4.5%
states 8
 
4.5%
richmond 3
 
1.7%
Other values (2) 2
 
1.1%
2023-12-09T23:27:52.933006image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 86
 
10.2%
e 69
 
8.2%
s 56
 
6.7%
S 48
 
5.7%
a 47
 
5.6%
U 46
 
5.5%
t 46
 
5.5%
i 40
 
4.8%
A 39
 
4.6%
o 36
 
4.3%
Other values (26) 328
39.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 562
66.8%
Uppercase Letter 246
29.3%
Space Separator 33
 
3.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 86
15.3%
e 69
12.3%
s 56
10.0%
a 47
8.4%
t 46
8.2%
i 40
7.1%
o 36
 
6.4%
r 33
 
5.9%
k 31
 
5.5%
g 28
 
5.0%
Other values (10) 90
16.0%
Uppercase Letter
ValueCountFrequency (%)
S 48
19.5%
U 46
18.7%
A 39
15.9%
N 25
10.2%
Y 23
9.3%
K 22
8.9%
Q 13
 
5.3%
M 10
 
4.1%
B 9
 
3.7%
R 4
 
1.6%
Other values (5) 7
 
2.8%
Space Separator
ValueCountFrequency (%)
33
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 808
96.1%
Common 33
 
3.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 86
 
10.6%
e 69
 
8.5%
s 56
 
6.9%
S 48
 
5.9%
a 47
 
5.8%
U 46
 
5.7%
t 46
 
5.7%
i 40
 
5.0%
A 39
 
4.8%
o 36
 
4.5%
Other values (25) 295
36.5%
Common
ValueCountFrequency (%)
33
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 841
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 86
 
10.2%
e 69
 
8.2%
s 56
 
6.7%
S 48
 
5.7%
a 47
 
5.6%
U 46
 
5.5%
t 46
 
5.5%
i 40
 
4.8%
A 39
 
4.6%
o 36
 
4.3%
Other values (26) 328
39.0%
Distinct154
Distinct (%)15.4%
Missing0
Missing (%)0.0%
Memory size60.7 KiB
2023-12-09T23:27:53.277182image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length10
Median length5
Mean length5.052
Min length5

Characters and Unicode

Total characters5052
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)4.0%

Sample

1st row10019
2nd row10465
3rd row11373
4th row10001-7507
5th row10001
ValueCountFrequency (%)
10001 38
 
3.8%
10016 35
 
3.5%
10018 35
 
3.5%
10452 30
 
3.0%
10462 29
 
2.9%
10453 27
 
2.7%
10017 27
 
2.7%
11101 25
 
2.5%
10036 24
 
2.4%
10019 22
 
2.2%
Other values (144) 708
70.8%
2023-12-09T23:27:53.732651image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1735
34.3%
0 1374
27.2%
2 430
 
8.5%
3 341
 
6.7%
4 333
 
6.6%
5 252
 
5.0%
6 237
 
4.7%
7 142
 
2.8%
8 136
 
2.7%
9 69
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5049
99.9%
Dash Punctuation 3
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1735
34.4%
0 1374
27.2%
2 430
 
8.5%
3 341
 
6.8%
4 333
 
6.6%
5 252
 
5.0%
6 237
 
4.7%
7 142
 
2.8%
8 136
 
2.7%
9 69
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5052
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1735
34.3%
0 1374
27.2%
2 430
 
8.5%
3 341
 
6.7%
4 333
 
6.6%
5 252
 
5.0%
6 237
 
4.7%
7 142
 
2.8%
8 136
 
2.7%
9 69
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5052
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1735
34.3%
0 1374
27.2%
2 430
 
8.5%
3 341
 
6.7%
4 333
 
6.6%
5 252
 
5.0%
6 237
 
4.7%
7 142
 
2.8%
8 136
 
2.7%
9 69
 
1.4%
Distinct36
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size71.3 KiB
2023-12-09T23:27:54.002851image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length37
Median length19
Mean length15.908
Min length5

Characters and Unicode

Total characters15908
Distinct characters48
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)0.4%

Sample

1st rowOffice
2nd rowNon-Refrigerated Warehouse
3rd rowK-12 School
4th rowHotel
5th rowHotel
ValueCountFrequency (%)
multifamily 497
27.8%
housing 497
27.8%
office 203
11.4%
hotel 51
 
2.9%
other 39
 
2.2%
warehouse 37
 
2.1%
29
 
1.6%
non-refrigerated 28
 
1.6%
college/university 21
 
1.2%
manufacturing/industrial 19
 
1.1%
Other values (47) 365
20.4%
2023-12-09T23:27:54.418442image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 2067
 
13.0%
l 1301
 
8.2%
u 1160
 
7.3%
f 972
 
6.1%
t 897
 
5.6%
a 824
 
5.2%
o 819
 
5.1%
e 794
 
5.0%
786
 
4.9%
n 758
 
4.8%
Other values (38) 5530
34.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 13038
82.0%
Uppercase Letter 1864
 
11.7%
Space Separator 786
 
4.9%
Other Punctuation 82
 
0.5%
Dash Punctuation 74
 
0.5%
Decimal Number 36
 
0.2%
Open Punctuation 14
 
0.1%
Close Punctuation 14
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 2067
15.9%
l 1301
10.0%
u 1160
8.9%
f 972
 
7.5%
t 897
 
6.9%
a 824
 
6.3%
o 819
 
6.3%
e 794
 
6.1%
n 758
 
5.8%
s 650
 
5.0%
Other values (12) 2796
21.4%
Uppercase Letter
ValueCountFrequency (%)
H 579
31.1%
M 548
29.4%
O 248
13.3%
S 88
 
4.7%
C 75
 
4.0%
R 59
 
3.2%
W 42
 
2.3%
P 38
 
2.0%
U 31
 
1.7%
D 29
 
1.6%
Other values (8) 127
 
6.8%
Other Punctuation
ValueCountFrequency (%)
/ 68
82.9%
& 14
 
17.1%
Decimal Number
ValueCountFrequency (%)
1 18
50.0%
2 18
50.0%
Space Separator
ValueCountFrequency (%)
786
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 74
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 14902
93.7%
Common 1006
 
6.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 2067
13.9%
l 1301
 
8.7%
u 1160
 
7.8%
f 972
 
6.5%
t 897
 
6.0%
a 824
 
5.5%
o 819
 
5.5%
e 794
 
5.3%
n 758
 
5.1%
s 650
 
4.4%
Other values (30) 4660
31.3%
Common
ValueCountFrequency (%)
786
78.1%
- 74
 
7.4%
/ 68
 
6.8%
1 18
 
1.8%
2 18
 
1.8%
( 14
 
1.4%
& 14
 
1.4%
) 14
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15908
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 2067
 
13.0%
l 1301
 
8.2%
u 1160
 
7.3%
f 972
 
6.1%
t 897
 
5.6%
a 824
 
5.2%
o 819
 
5.1%
e 794
 
5.0%
786
 
4.9%
n 758
 
4.8%
Other values (38) 5530
34.8%
Distinct36
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size71.3 KiB
2023-12-09T23:27:54.695222image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length37
Median length19
Mean length15.848
Min length5

Characters and Unicode

Total characters15848
Distinct characters48
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)0.3%

Sample

1st rowOffice
2nd rowNon-Refrigerated Warehouse
3rd rowK-12 School
4th rowHotel
5th rowHotel
ValueCountFrequency (%)
multifamily 498
27.9%
housing 498
27.9%
office 202
11.3%
hotel 51
 
2.9%
other 44
 
2.5%
warehouse 38
 
2.1%
30
 
1.7%
non-refrigerated 29
 
1.6%
college/university 21
 
1.2%
manufacturing/industrial 18
 
1.0%
Other values (47) 356
19.9%
2023-12-09T23:27:55.119211image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 2050
 
12.9%
l 1296
 
8.2%
u 1155
 
7.3%
f 971
 
6.1%
t 883
 
5.6%
a 817
 
5.2%
o 817
 
5.2%
e 801
 
5.1%
785
 
5.0%
n 747
 
4.7%
Other values (38) 5526
34.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 12985
81.9%
Uppercase Letter 1861
 
11.7%
Space Separator 785
 
5.0%
Other Punctuation 80
 
0.5%
Dash Punctuation 75
 
0.5%
Decimal Number 34
 
0.2%
Close Punctuation 14
 
0.1%
Open Punctuation 14
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 2050
15.8%
l 1296
10.0%
u 1155
8.9%
f 971
 
7.5%
t 883
 
6.8%
a 817
 
6.3%
o 817
 
6.3%
e 801
 
6.2%
n 747
 
5.8%
s 649
 
5.0%
Other values (12) 2799
21.6%
Uppercase Letter
ValueCountFrequency (%)
H 579
31.1%
M 552
29.7%
O 250
13.4%
S 85
 
4.6%
C 69
 
3.7%
R 60
 
3.2%
P 41
 
2.2%
W 41
 
2.2%
U 34
 
1.8%
N 29
 
1.6%
Other values (8) 121
 
6.5%
Other Punctuation
ValueCountFrequency (%)
/ 66
82.5%
& 14
 
17.5%
Decimal Number
ValueCountFrequency (%)
1 17
50.0%
2 17
50.0%
Space Separator
ValueCountFrequency (%)
785
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 75
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 14846
93.7%
Common 1002
 
6.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 2050
13.8%
l 1296
 
8.7%
u 1155
 
7.8%
f 971
 
6.5%
t 883
 
5.9%
a 817
 
5.5%
o 817
 
5.5%
e 801
 
5.4%
n 747
 
5.0%
s 649
 
4.4%
Other values (30) 4660
31.4%
Common
ValueCountFrequency (%)
785
78.3%
- 75
 
7.5%
/ 66
 
6.6%
1 17
 
1.7%
2 17
 
1.7%
) 14
 
1.4%
& 14
 
1.4%
( 14
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15848
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 2050
 
12.9%
l 1296
 
8.2%
u 1155
 
7.3%
f 971
 
6.1%
t 883
 
5.6%
a 817
 
5.2%
o 817
 
5.2%
e 801
 
5.1%
785
 
5.0%
n 747
 
4.7%
Other values (38) 5526
34.9%
Distinct26
Distinct (%)2.7%
Missing21
Missing (%)2.1%
Memory size88.4 KiB
2023-12-09T23:27:55.343532image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length54
Median length40
Mean length34.68232891
Min length13

Characters and Unicode

Total characters33954
Distinct characters42
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)0.3%

Sample

1st rowCBECS - Office & Bank/Financial
2nd rowCBECS - Unrefrigerated Warehouse & Distribution Center
3rd rowCBECS - Elementary/Middle & High School
4th rowCBECS - Hotel & Motel/Inn
5th rowCBECS - Hotel & Motel/Inn
ValueCountFrequency (%)
1298
24.7%
fannie 498
 
9.5%
industry 498
 
9.5%
survey 498
 
9.5%
multifamily 498
 
9.5%
mae 498
 
9.5%
cbecs 472
 
9.0%
office 202
 
3.9%
bank/financial 200
 
3.8%
warehouse 60
 
1.1%
Other values (40) 523
10.0%
2023-12-09T23:27:55.687374image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4266
 
12.6%
i 2444
 
7.2%
e 2442
 
7.2%
n 2440
 
7.2%
a 2325
 
6.8%
u 1634
 
4.8%
y 1555
 
4.6%
r 1476
 
4.3%
t 1469
 
4.3%
l 1461
 
4.3%
Other values (32) 12442
36.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 21938
64.6%
Uppercase Letter 6160
 
18.1%
Space Separator 4266
 
12.6%
Dash Punctuation 979
 
2.9%
Other Punctuation 611
 
1.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 2444
11.1%
e 2442
11.1%
n 2440
11.1%
a 2325
10.6%
u 1634
7.4%
y 1555
7.1%
r 1476
 
6.7%
t 1469
 
6.7%
l 1461
 
6.7%
f 963
 
4.4%
Other values (11) 3729
17.0%
Uppercase Letter
ValueCountFrequency (%)
M 1073
17.4%
S 1026
16.7%
C 1016
16.5%
F 700
11.4%
B 672
10.9%
I 575
9.3%
E 507
8.2%
O 248
 
4.0%
H 86
 
1.4%
U 81
 
1.3%
Other values (7) 176
 
2.9%
Other Punctuation
ValueCountFrequency (%)
& 319
52.2%
/ 292
47.8%
Space Separator
ValueCountFrequency (%)
4266
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 979
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 28098
82.8%
Common 5856
 
17.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 2444
 
8.7%
e 2442
 
8.7%
n 2440
 
8.7%
a 2325
 
8.3%
u 1634
 
5.8%
y 1555
 
5.5%
r 1476
 
5.3%
t 1469
 
5.2%
l 1461
 
5.2%
M 1073
 
3.8%
Other values (28) 9779
34.8%
Common
ValueCountFrequency (%)
4266
72.8%
- 979
 
16.7%
& 319
 
5.4%
/ 292
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 33954
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4266
 
12.6%
i 2444
 
7.2%
e 2442
 
7.2%
n 2440
 
7.2%
a 2325
 
6.8%
u 1634
 
4.8%
y 1555
 
4.6%
r 1476
 
4.3%
t 1469
 
4.3%
l 1461
 
4.3%
Other values (32) 12442
36.6%
Distinct159
Distinct (%)15.9%
Missing0
Missing (%)0.0%
Memory size78.1 KiB
2023-12-09T23:27:55.986849image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length157
Median length156
Mean length22.876
Min length5

Characters and Unicode

Total characters22876
Distinct characters53
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique91 ?
Unique (%)9.1%

Sample

1st rowBank Branch, Office
2nd rowNon-Refrigerated Warehouse
3rd rowK-12 School
4th rowHotel
5th rowHotel
ValueCountFrequency (%)
multifamily 501
19.3%
housing 501
19.3%
office 277
 
10.7%
other 120
 
4.6%
store 113
 
4.4%
retail 87
 
3.4%
parking 66
 
2.5%
57
 
2.2%
hotel 53
 
2.0%
restaurant 50
 
1.9%
Other values (83) 770
29.7%
2023-12-09T23:27:56.475259image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 2451
 
10.7%
1595
 
7.0%
l 1520
 
6.6%
e 1491
 
6.5%
t 1455
 
6.4%
a 1377
 
6.0%
u 1298
 
5.7%
f 1138
 
5.0%
n 1077
 
4.7%
o 1062
 
4.6%
Other values (43) 8412
36.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 17744
77.6%
Uppercase Letter 2714
 
11.9%
Space Separator 1595
 
7.0%
Other Punctuation 628
 
2.7%
Dash Punctuation 113
 
0.5%
Decimal Number 40
 
0.2%
Open Punctuation 21
 
0.1%
Close Punctuation 21
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 2451
13.8%
l 1520
 
8.6%
e 1491
 
8.4%
t 1455
 
8.2%
a 1377
 
7.8%
u 1298
 
7.3%
f 1138
 
6.4%
n 1077
 
6.1%
o 1062
 
6.0%
r 915
 
5.2%
Other values (12) 3960
22.3%
Uppercase Letter
ValueCountFrequency (%)
H 602
22.2%
M 576
21.2%
O 408
15.0%
S 244
9.0%
R 223
 
8.2%
P 114
 
4.2%
C 111
 
4.1%
F 83
 
3.1%
B 61
 
2.2%
W 55
 
2.0%
Other values (11) 237
 
8.7%
Other Punctuation
ValueCountFrequency (%)
, 467
74.4%
/ 140
 
22.3%
& 14
 
2.2%
. 7
 
1.1%
Decimal Number
ValueCountFrequency (%)
2 20
50.0%
1 20
50.0%
Space Separator
ValueCountFrequency (%)
1595
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 113
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 20458
89.4%
Common 2418
 
10.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 2451
 
12.0%
l 1520
 
7.4%
e 1491
 
7.3%
t 1455
 
7.1%
a 1377
 
6.7%
u 1298
 
6.3%
f 1138
 
5.6%
n 1077
 
5.3%
o 1062
 
5.2%
r 915
 
4.5%
Other values (33) 6674
32.6%
Common
ValueCountFrequency (%)
1595
66.0%
, 467
 
19.3%
/ 140
 
5.8%
- 113
 
4.7%
( 21
 
0.9%
) 21
 
0.9%
2 20
 
0.8%
1 20
 
0.8%
& 14
 
0.6%
. 7
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22876
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 2451
 
10.7%
1595
 
7.0%
l 1520
 
6.6%
e 1491
 
6.5%
t 1455
 
6.4%
a 1377
 
6.0%
u 1298
 
5.7%
f 1138
 
5.0%
n 1077
 
4.7%
o 1062
 
4.6%
Other values (43) 8412
36.8%
Distinct35
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size71.2 KiB
2023-12-09T23:27:56.741612image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length37
Median length19
Mean length15.816
Min length5

Characters and Unicode

Total characters15816
Distinct characters47
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)0.3%

Sample

1st rowOffice
2nd rowNon-Refrigerated Warehouse
3rd rowK-12 School
4th rowHotel
5th rowHotel
ValueCountFrequency (%)
multifamily 498
28.1%
housing 498
28.1%
office 204
11.5%
hotel 51
 
2.9%
other 49
 
2.8%
warehouse 38
 
2.1%
31
 
1.7%
non-refrigerated 29
 
1.6%
college/university 21
 
1.2%
manufacturing/industrial 19
 
1.1%
Other values (44) 334
18.8%
2023-12-09T23:27:57.150773image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 2055
 
13.0%
l 1303
 
8.2%
u 1160
 
7.3%
f 976
 
6.2%
t 891
 
5.6%
a 827
 
5.2%
o 809
 
5.1%
e 783
 
5.0%
772
 
4.9%
n 756
 
4.8%
Other values (37) 5484
34.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 12973
82.0%
Uppercase Letter 1850
 
11.7%
Space Separator 772
 
4.9%
Other Punctuation 83
 
0.5%
Dash Punctuation 76
 
0.5%
Decimal Number 34
 
0.2%
Close Punctuation 14
 
0.1%
Open Punctuation 14
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 2055
15.8%
l 1303
10.0%
u 1160
8.9%
f 976
 
7.5%
t 891
 
6.9%
a 827
 
6.4%
o 809
 
6.2%
e 783
 
6.0%
n 756
 
5.8%
s 642
 
4.9%
Other values (11) 2771
21.4%
Uppercase Letter
ValueCountFrequency (%)
H 580
31.4%
M 543
29.4%
O 259
14.0%
S 86
 
4.6%
C 72
 
3.9%
R 60
 
3.2%
W 42
 
2.3%
P 31
 
1.7%
N 29
 
1.6%
D 26
 
1.4%
Other values (8) 122
 
6.6%
Other Punctuation
ValueCountFrequency (%)
/ 69
83.1%
& 14
 
16.9%
Decimal Number
ValueCountFrequency (%)
1 17
50.0%
2 17
50.0%
Space Separator
ValueCountFrequency (%)
772
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 76
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 14823
93.7%
Common 993
 
6.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 2055
13.9%
l 1303
 
8.8%
u 1160
 
7.8%
f 976
 
6.6%
t 891
 
6.0%
a 827
 
5.6%
o 809
 
5.5%
e 783
 
5.3%
n 756
 
5.1%
s 642
 
4.3%
Other values (29) 4621
31.2%
Common
ValueCountFrequency (%)
772
77.7%
- 76
 
7.7%
/ 69
 
6.9%
1 17
 
1.7%
2 17
 
1.7%
& 14
 
1.4%
) 14
 
1.4%
( 14
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15816
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 2055
 
13.0%
l 1303
 
8.2%
u 1160
 
7.3%
f 976
 
6.2%
t 891
 
5.6%
a 827
 
5.2%
o 809
 
5.1%
e 783
 
5.0%
772
 
4.9%
n 756
 
4.8%
Other values (37) 5484
34.7%
Distinct788
Distinct (%)78.8%
Missing0
Missing (%)0.0%
Memory size61.1 KiB
2023-12-09T23:27:57.558569image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length8
Median length5
Mean length5.441
Min length4

Characters and Unicode

Total characters5441
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique663 ?
Unique (%)66.3%

Sample

1st row164754
2nd row104407
3rd row94380
4th row125000
5th row50000
ValueCountFrequency (%)
60000 9
 
0.9%
57000 8
 
0.8%
50000 8
 
0.8%
150000 7
 
0.7%
80000 7
 
0.7%
40000 6
 
0.6%
54000 6
 
0.6%
280358 6
 
0.6%
200000 5
 
0.5%
65968 5
 
0.5%
Other values (778) 933
93.3%
2023-12-09T23:27:58.113415image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1409
25.9%
1 561
 
10.3%
5 537
 
9.9%
2 472
 
8.7%
6 462
 
8.5%
8 434
 
8.0%
4 419
 
7.7%
3 412
 
7.6%
7 403
 
7.4%
9 327
 
6.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5436
99.9%
Other Punctuation 5
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1409
25.9%
1 561
 
10.3%
5 537
 
9.9%
2 472
 
8.7%
6 462
 
8.5%
8 434
 
8.0%
4 419
 
7.7%
3 412
 
7.6%
7 403
 
7.4%
9 327
 
6.0%
Other Punctuation
ValueCountFrequency (%)
. 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5441
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1409
25.9%
1 561
 
10.3%
5 537
 
9.9%
2 472
 
8.7%
6 462
 
8.5%
8 434
 
8.0%
4 419
 
7.7%
3 412
 
7.6%
7 403
 
7.4%
9 327
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5441
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1409
25.9%
1 561
 
10.3%
5 537
 
9.9%
2 472
 
8.7%
6 462
 
8.5%
8 434
 
8.0%
4 419
 
7.7%
3 412
 
7.6%
7 403
 
7.4%
9 327
 
6.0%
Distinct31
Distinct (%)12.0%
Missing742
Missing (%)74.2%
Memory size40.7 KiB
2023-12-09T23:27:58.388836image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length42
Median length35
Mean length12.1744186
Min length5

Characters and Unicode

Total characters3141
Distinct characters47
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)4.3%

Sample

1st rowBank Branch
2nd rowOther - Recreation
3rd rowSupermarket/Grocery Store
4th rowRefrigerated Warehouse
5th rowRefrigerated Warehouse
ValueCountFrequency (%)
store 75
17.1%
retail 65
14.8%
parking 52
11.8%
office 41
 
9.3%
other 34
 
7.7%
restaurant 19
 
4.3%
14
 
3.2%
medical 12
 
2.7%
bank 11
 
2.5%
branch 11
 
2.5%
Other values (40) 105
23.9%
2023-12-09T23:27:58.803694image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 353
 
11.2%
t 295
 
9.4%
a 287
 
9.1%
r 282
 
9.0%
i 235
 
7.5%
181
 
5.8%
n 155
 
4.9%
o 134
 
4.3%
l 115
 
3.7%
R 101
 
3.2%
Other values (37) 1003
31.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2453
78.1%
Uppercase Letter 454
 
14.5%
Space Separator 181
 
5.8%
Other Punctuation 26
 
0.8%
Dash Punctuation 21
 
0.7%
Decimal Number 6
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 353
14.4%
t 295
12.0%
a 287
11.7%
r 282
11.5%
i 235
9.6%
n 155
 
6.3%
o 134
 
5.5%
l 115
 
4.7%
c 98
 
4.0%
f 93
 
3.8%
Other values (12) 406
16.6%
Uppercase Letter
ValueCountFrequency (%)
R 101
22.2%
S 90
19.8%
O 78
17.2%
P 57
12.6%
B 28
 
6.2%
F 27
 
5.9%
M 18
 
4.0%
G 12
 
2.6%
C 11
 
2.4%
H 7
 
1.5%
Other values (10) 25
 
5.5%
Decimal Number
ValueCountFrequency (%)
1 3
50.0%
2 3
50.0%
Space Separator
ValueCountFrequency (%)
181
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 26
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2907
92.6%
Common 234
 
7.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 353
12.1%
t 295
 
10.1%
a 287
 
9.9%
r 282
 
9.7%
i 235
 
8.1%
n 155
 
5.3%
o 134
 
4.6%
l 115
 
4.0%
R 101
 
3.5%
c 98
 
3.4%
Other values (32) 852
29.3%
Common
ValueCountFrequency (%)
181
77.4%
/ 26
 
11.1%
- 21
 
9.0%
1 3
 
1.3%
2 3
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3141
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 353
 
11.2%
t 295
 
9.4%
a 287
 
9.1%
r 282
 
9.0%
i 235
 
7.5%
181
 
5.8%
n 155
 
4.9%
o 134
 
4.3%
l 115
 
3.7%
R 101
 
3.2%
Other values (37) 1003
31.9%
Distinct197
Distinct (%)76.4%
Missing742
Missing (%)74.2%
Memory size38.8 KiB
2023-12-09T23:27:59.230433image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length6
Mean length4.403100775
Min length1

Characters and Unicode

Total characters1136
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique173 ?
Unique (%)67.1%

Sample

1st row4662
2nd row28006
3rd row13799
4th row190000
5th row190000
ValueCountFrequency (%)
0 19
 
7.4%
10000 9
 
3.5%
20000 7
 
2.7%
5000 5
 
1.9%
2000 4
 
1.6%
7500 3
 
1.2%
33785 3
 
1.2%
6750 3
 
1.2%
31625 2
 
0.8%
32063 2
 
0.8%
Other values (187) 201
77.9%
2023-12-09T23:27:59.804801image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 346
30.5%
1 128
 
11.3%
2 113
 
9.9%
5 106
 
9.3%
3 96
 
8.5%
4 84
 
7.4%
7 67
 
5.9%
6 66
 
5.8%
8 64
 
5.6%
9 63
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1133
99.7%
Other Punctuation 3
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 346
30.5%
1 128
 
11.3%
2 113
 
10.0%
5 106
 
9.4%
3 96
 
8.5%
4 84
 
7.4%
7 67
 
5.9%
6 66
 
5.8%
8 64
 
5.6%
9 63
 
5.6%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1136
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 346
30.5%
1 128
 
11.3%
2 113
 
9.9%
5 106
 
9.3%
3 96
 
8.5%
4 84
 
7.4%
7 67
 
5.9%
6 66
 
5.8%
8 64
 
5.6%
9 63
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1136
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 346
30.5%
1 128
 
11.3%
2 113
 
9.9%
5 106
 
9.3%
3 96
 
8.5%
4 84
 
7.4%
7 67
 
5.9%
6 66
 
5.8%
8 64
 
5.6%
9 63
 
5.5%
Distinct24
Distinct (%)22.0%
Missing891
Missing (%)89.1%
Memory size35.4 KiB
2023-12-09T23:28:00.070063image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length53
Median length26
Mean length13.26605505
Min length5

Characters and Unicode

Total characters1446
Distinct characters45
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)7.3%

Sample

1st rowOffice
2nd rowNon-Refrigerated Warehouse
3rd rowRetail Store
4th rowFood Sales
5th rowOffice
ValueCountFrequency (%)
office 21
 
11.0%
other 20
 
10.5%
restaurant 18
 
9.4%
store 16
 
8.4%
retail 11
 
5.8%
food 9
 
4.7%
parking 7
 
3.7%
medical 6
 
3.1%
bank 5
 
2.6%
branch 5
 
2.6%
Other values (34) 73
38.2%
2023-12-09T23:28:00.463926image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 174
 
12.0%
a 132
 
9.1%
t 132
 
9.1%
r 118
 
8.2%
82
 
5.7%
i 77
 
5.3%
n 69
 
4.8%
o 53
 
3.7%
l 49
 
3.4%
c 48
 
3.3%
Other values (35) 512
35.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1119
77.4%
Uppercase Letter 208
 
14.4%
Space Separator 82
 
5.7%
Other Punctuation 26
 
1.8%
Dash Punctuation 7
 
0.5%
Open Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 174
15.5%
a 132
11.8%
t 132
11.8%
r 118
10.5%
i 77
 
6.9%
n 69
 
6.2%
o 53
 
4.7%
l 49
 
4.4%
c 48
 
4.3%
s 48
 
4.3%
Other values (12) 219
19.6%
Uppercase Letter
ValueCountFrequency (%)
O 42
20.2%
R 37
17.8%
S 29
13.9%
F 23
11.1%
B 16
 
7.7%
C 12
 
5.8%
P 10
 
4.8%
G 9
 
4.3%
M 8
 
3.8%
H 8
 
3.8%
Other values (6) 14
 
6.7%
Other Punctuation
ValueCountFrequency (%)
/ 20
76.9%
, 4
 
15.4%
. 2
 
7.7%
Space Separator
ValueCountFrequency (%)
82
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1327
91.8%
Common 119
 
8.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 174
13.1%
a 132
 
9.9%
t 132
 
9.9%
r 118
 
8.9%
i 77
 
5.8%
n 69
 
5.2%
o 53
 
4.0%
l 49
 
3.7%
c 48
 
3.6%
s 48
 
3.6%
Other values (28) 427
32.2%
Common
ValueCountFrequency (%)
82
68.9%
/ 20
 
16.8%
- 7
 
5.9%
, 4
 
3.4%
( 2
 
1.7%
. 2
 
1.7%
) 2
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1446
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 174
 
12.0%
a 132
 
9.1%
t 132
 
9.1%
r 118
 
8.2%
82
 
5.7%
i 77
 
5.3%
n 69
 
4.8%
o 53
 
3.7%
l 49
 
3.4%
c 48
 
3.3%
Other values (35) 512
35.4%
Distinct85
Distinct (%)78.0%
Missing891
Missing (%)89.1%
Memory size34.5 KiB
2023-12-09T23:28:00.791747image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.174311927
Min length1

Characters and Unicode

Total characters455
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique70 ?
Unique (%)64.2%

Sample

1st row9134
2nd row4455
3rd row60015
4th row355.6
5th row8700
ValueCountFrequency (%)
0 6
 
5.5%
4200 3
 
2.8%
10000 3
 
2.8%
5125 3
 
2.8%
5000 3
 
2.8%
1000 3
 
2.8%
30260 2
 
1.8%
8000 2
 
1.8%
7296 2
 
1.8%
26155 2
 
1.8%
Other values (75) 80
73.4%
2023-12-09T23:28:01.249565image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 116
25.5%
1 59
13.0%
2 55
12.1%
5 51
11.2%
3 35
 
7.7%
8 34
 
7.5%
7 30
 
6.6%
4 27
 
5.9%
9 25
 
5.5%
6 22
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 454
99.8%
Other Punctuation 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 116
25.6%
1 59
13.0%
2 55
12.1%
5 51
11.2%
3 35
 
7.7%
8 34
 
7.5%
7 30
 
6.6%
4 27
 
5.9%
9 25
 
5.5%
6 22
 
4.8%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 455
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 116
25.5%
1 59
13.0%
2 55
12.1%
5 51
11.2%
3 35
 
7.7%
8 34
 
7.5%
7 30
 
6.6%
4 27
 
5.9%
9 25
 
5.5%
6 22
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 455
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 116
25.5%
1 59
13.0%
2 55
12.1%
5 51
11.2%
3 35
 
7.7%
8 34
 
7.5%
7 30
 
6.6%
4 27
 
5.9%
9 25
 
5.5%
6 22
 
4.8%
Distinct126
Distinct (%)12.6%
Missing0
Missing (%)0.0%
Memory size59.7 KiB
2023-12-09T23:28:01.630065image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters4000
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)1.9%

Sample

1st row1909
2nd row1973
3rd row1963
4th row1999
5th row1994
ValueCountFrequency (%)
1926 38
 
3.8%
1940 35
 
3.5%
1931 35
 
3.5%
1927 33
 
3.3%
1930 31
 
3.1%
1920 29
 
2.9%
1928 27
 
2.7%
1960 26
 
2.6%
1910 25
 
2.5%
1950 24
 
2.4%
Other values (116) 697
69.7%
2023-12-09T23:28:02.118007image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1114
27.9%
9 1013
25.3%
0 460
11.5%
2 431
 
10.8%
6 197
 
4.9%
5 184
 
4.6%
3 181
 
4.5%
8 158
 
4.0%
7 135
 
3.4%
4 127
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1114
27.9%
9 1013
25.3%
0 460
11.5%
2 431
 
10.8%
6 197
 
4.9%
5 184
 
4.6%
3 181
 
4.5%
8 158
 
4.0%
7 135
 
3.4%
4 127
 
3.2%

Most occurring scripts

ValueCountFrequency (%)
Common 4000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1114
27.9%
9 1013
25.3%
0 460
11.5%
2 431
 
10.8%
6 197
 
4.9%
5 184
 
4.6%
3 181
 
4.5%
8 158
 
4.0%
7 135
 
3.4%
4 127
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1114
27.9%
9 1013
25.3%
0 460
11.5%
2 431
 
10.8%
6 197
 
4.9%
5 184
 
4.6%
3 181
 
4.5%
8 158
 
4.0%
7 135
 
3.4%
4 127
 
3.2%
Distinct15
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T23:28:02.263753image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.006
Min length1

Characters and Unicode

Total characters1006
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)0.7%

Sample

1st row1
2nd row2
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
1 947
94.7%
2 21
 
2.1%
3 7
 
0.7%
8 5
 
0.5%
4 5
 
0.5%
0 4
 
0.4%
6 2
 
0.2%
5 2
 
0.2%
38 1
 
0.1%
11 1
 
0.1%
Other values (5) 5
 
0.5%
2023-12-09T23:28:02.501351image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 950
94.4%
2 23
 
2.3%
3 9
 
0.9%
8 7
 
0.7%
4 7
 
0.7%
0 5
 
0.5%
6 2
 
0.2%
5 2
 
0.2%
9 1
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1006
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 950
94.4%
2 23
 
2.3%
3 9
 
0.9%
8 7
 
0.7%
4 7
 
0.7%
0 5
 
0.5%
6 2
 
0.2%
5 2
 
0.2%
9 1
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 1006
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 950
94.4%
2 23
 
2.3%
3 9
 
0.9%
8 7
 
0.7%
4 7
 
0.7%
0 5
 
0.5%
6 2
 
0.2%
5 2
 
0.2%
9 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1006
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 950
94.4%
2 23
 
2.3%
3 9
 
0.9%
8 7
 
0.7%
4 7
 
0.7%
0 5
 
0.5%
6 2
 
0.2%
5 2
 
0.2%
9 1
 
0.1%
Distinct16
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size58.6 KiB
2023-12-09T23:28:02.641022image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.837
Min length1

Characters and Unicode

Total characters2837
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)0.5%

Sample

1st row95
2nd row100
3rd row100
4th row85
5th row100
ValueCountFrequency (%)
100 844
84.4%
95 53
 
5.3%
90 45
 
4.5%
85 17
 
1.7%
80 12
 
1.2%
70 7
 
0.7%
0 7
 
0.7%
75 4
 
0.4%
50 2
 
0.2%
25 2
 
0.2%
Other values (6) 7
 
0.7%
2023-12-09T23:28:02.926069image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1764
62.2%
1 845
29.8%
9 98
 
3.5%
5 83
 
2.9%
8 29
 
1.0%
7 11
 
0.4%
6 3
 
0.1%
2 2
 
0.1%
4 1
 
< 0.1%
3 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2837
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1764
62.2%
1 845
29.8%
9 98
 
3.5%
5 83
 
2.9%
8 29
 
1.0%
7 11
 
0.4%
6 3
 
0.1%
2 2
 
0.1%
4 1
 
< 0.1%
3 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 2837
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1764
62.2%
1 845
29.8%
9 98
 
3.5%
5 83
 
2.9%
8 29
 
1.0%
7 11
 
0.4%
6 3
 
0.1%
2 2
 
0.1%
4 1
 
< 0.1%
3 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2837
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1764
62.2%
1 845
29.8%
9 98
 
3.5%
5 83
 
2.9%
8 29
 
1.0%
7 11
 
0.4%
6 3
 
0.1%
2 2
 
0.1%
4 1
 
< 0.1%
3 1
 
< 0.1%

metered_areas_energy
Text

MISSING 

Distinct4
Distinct (%)0.4%
Missing40
Missing (%)4.0%
Memory size68.1 KiB
2023-12-09T23:28:03.128694image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length132
Median length14
Mean length14.21875
Min length14

Characters and Unicode

Total characters13650
Distinct characters31
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)0.2%

Sample

1st rowWhole Building
2nd rowWhole Building
3rd rowWhole Building
4th rowWhole Building
5th rowWhole Building
ValueCountFrequency (%)
whole 953
48.8%
building 953
48.8%
common 9
 
0.5%
areas 5
 
0.3%
all 5
 
0.3%
energy 5
 
0.3%
loads 5
 
0.3%
area 4
 
0.2%
heating 2
 
0.1%
hot 2
 
0.1%
Other values (7) 9
 
0.5%
2023-12-09T23:28:03.793349image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
l 1924
14.1%
i 1913
14.0%
992
7.3%
o 984
7.2%
e 980
7.2%
n 977
7.2%
g 963
7.1%
d 959
7.0%
W 955
7.0%
u 955
7.0%
Other values (21) 2048
15.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 10710
78.5%
Uppercase Letter 1932
 
14.2%
Space Separator 992
 
7.3%
Other Punctuation 6
 
< 0.1%
Open Punctuation 5
 
< 0.1%
Close Punctuation 5
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
l 1924
18.0%
i 1913
17.9%
o 984
9.2%
e 980
9.2%
n 977
9.1%
g 963
9.0%
d 959
9.0%
u 955
8.9%
h 954
8.9%
a 32
 
0.3%
Other values (7) 69
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
W 955
49.4%
B 953
49.3%
C 10
 
0.5%
A 5
 
0.3%
H 4
 
0.2%
T 2
 
0.1%
P 1
 
0.1%
L 1
 
0.1%
E 1
 
0.1%
Other Punctuation
ValueCountFrequency (%)
, 5
83.3%
/ 1
 
16.7%
Space Separator
ValueCountFrequency (%)
992
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 12642
92.6%
Common 1008
 
7.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
l 1924
15.2%
i 1913
15.1%
o 984
7.8%
e 980
7.8%
n 977
7.7%
g 963
7.6%
d 959
7.6%
W 955
7.6%
u 955
7.6%
h 954
7.5%
Other values (16) 1078
8.5%
Common
ValueCountFrequency (%)
992
98.4%
, 5
 
0.5%
( 5
 
0.5%
) 5
 
0.5%
/ 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13650
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
l 1924
14.1%
i 1913
14.0%
992
7.3%
o 984
7.2%
e 980
7.2%
n 977
7.2%
g 963
7.1%
d 959
7.0%
W 955
7.0%
u 955
7.0%
Other values (21) 2048
15.0%

metered_areas_water
Text

MISSING 

Distinct4
Distinct (%)0.7%
Missing410
Missing (%)41.0%
Memory size53.9 KiB
2023-12-09T23:28:03.979635image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length49
Median length14
Mean length14.11694915
Min length14

Characters and Unicode

Total characters8329
Distinct characters25
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)0.5%

Sample

1st rowWhole Building
2nd rowWhole Building
3rd rowWhole Building
4th rowWhole Building
5th rowTenant areas (all energy loads)
ValueCountFrequency (%)
whole 587
49.3%
building 587
49.3%
areas 3
 
0.3%
energy 3
 
0.3%
loads 3
 
0.3%
common 2
 
0.2%
all 2
 
0.2%
tenant 2
 
0.2%
and/or 1
 
0.1%
partial 1
 
0.1%
2023-12-09T23:28:04.296255image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
l 1182
14.2%
i 1175
14.1%
601
7.2%
e 598
7.2%
n 597
7.2%
o 595
7.1%
d 591
7.1%
g 590
7.1%
h 587
7.0%
W 587
7.0%
Other values (15) 1226
14.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 6544
78.6%
Uppercase Letter 1177
 
14.1%
Space Separator 601
 
7.2%
Open Punctuation 3
 
< 0.1%
Close Punctuation 3
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
l 1182
18.1%
i 1175
18.0%
e 598
9.1%
n 597
9.1%
o 595
9.1%
d 591
9.0%
g 590
9.0%
h 587
9.0%
u 587
9.0%
a 16
 
0.2%
Other values (7) 26
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
W 587
49.9%
B 587
49.9%
T 2
 
0.2%
C 1
 
0.1%
Space Separator
ValueCountFrequency (%)
601
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 7721
92.7%
Common 608
 
7.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
l 1182
15.3%
i 1175
15.2%
e 598
7.7%
n 597
7.7%
o 595
7.7%
d 591
7.7%
g 590
7.6%
h 587
7.6%
W 587
7.6%
u 587
7.6%
Other values (11) 632
8.2%
Common
ValueCountFrequency (%)
601
98.8%
( 3
 
0.5%
) 3
 
0.5%
/ 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8329
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
l 1182
14.2%
i 1175
14.1%
601
7.2%
e 598
7.2%
n 597
7.2%
o 595
7.1%
d 591
7.1%
g 590
7.1%
h 587
7.0%
W 587
7.0%
Other values (15) 1226
14.7%

energy_star_score
Text

MISSING 

Distinct98
Distinct (%)14.0%
Missing301
Missing (%)30.1%
Memory size49.8 KiB
2023-12-09T23:28:04.615087image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length1.995708155
Min length1

Characters and Unicode

Total characters1395
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)0.6%

Sample

1st row90
2nd row100
3rd row83
4th row27
5th row99
ValueCountFrequency (%)
100 53
 
7.6%
88 19
 
2.7%
97 16
 
2.3%
91 15
 
2.1%
83 14
 
2.0%
85 14
 
2.0%
76 14
 
2.0%
90 14
 
2.0%
1 13
 
1.9%
70 13
 
1.9%
Other values (88) 514
73.5%
2023-12-09T23:28:05.080669image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 192
13.8%
9 171
12.3%
0 170
12.2%
7 160
11.5%
1 159
11.4%
5 127
9.1%
6 114
8.2%
4 106
7.6%
3 105
7.5%
2 91
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1395
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 192
13.8%
9 171
12.3%
0 170
12.2%
7 160
11.5%
1 159
11.4%
5 127
9.1%
6 114
8.2%
4 106
7.6%
3 105
7.5%
2 91
6.5%

Most occurring scripts

ValueCountFrequency (%)
Common 1395
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 192
13.8%
9 171
12.3%
0 170
12.2%
7 160
11.5%
1 159
11.4%
5 127
9.1%
6 114
8.2%
4 106
7.6%
3 105
7.5%
2 91
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1395
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 192
13.8%
9 171
12.3%
0 170
12.2%
7 160
11.5%
1 159
11.4%
5 127
9.1%
6 114
8.2%
4 106
7.6%
3 105
7.5%
2 91
6.5%
Distinct33
Distinct (%)55.0%
Missing940
Missing (%)94.0%
Memory size33.6 KiB
2023-12-09T23:28:05.334343image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length36
Median length28
Mean length13.4
Min length4

Characters and Unicode

Total characters804
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)40.0%

Sample

1st row20172016
2nd row20172016
3rd row20172016
4th row20152013
5th row2017201620152014201320102008
ValueCountFrequency (%)
2017 11
18.3%
201720162015 7
 
11.7%
20172016 5
 
8.3%
201720162015201420132012 3
 
5.0%
2016201520142013 2
 
3.3%
2017201620152013201220102009 2
 
3.3%
2017201620152014201320102008 2
 
3.3%
20162015 2
 
3.3%
2015 2
 
3.3%
2018201720162014201320122010 1
 
1.7%
Other values (23) 23
38.3%
2023-12-09T23:28:05.709275image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 220
27.4%
2 219
27.2%
1 196
24.4%
7 47
 
5.8%
6 36
 
4.5%
5 31
 
3.9%
3 24
 
3.0%
4 19
 
2.4%
9 7
 
0.9%
8 5
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 804
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 220
27.4%
2 219
27.2%
1 196
24.4%
7 47
 
5.8%
6 36
 
4.5%
5 31
 
3.9%
3 24
 
3.0%
4 19
 
2.4%
9 7
 
0.9%
8 5
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
Common 804
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 220
27.4%
2 219
27.2%
1 196
24.4%
7 47
 
5.8%
6 36
 
4.5%
5 31
 
3.9%
3 24
 
3.0%
4 19
 
2.4%
9 7
 
0.9%
8 5
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 804
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 220
27.4%
2 219
27.2%
1 196
24.4%
7 47
 
5.8%
6 36
 
4.5%
5 31
 
3.9%
3 24
 
3.0%
4 19
 
2.4%
9 7
 
0.9%
8 5
 
0.6%
Distinct47
Distinct (%)78.3%
Missing940
Missing (%)94.0%
Memory size34.2 KiB
2023-12-09T23:28:05.969367image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length23
Median length23
Mean length23
Min length23

Characters and Unicode

Total characters1380
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)61.7%

Sample

1st row2017-02-28T00:00:00.000
2nd row2017-07-06T00:00:00.000
3rd row2017-09-01T00:00:00.000
4th row2015-12-10T00:00:00.000
5th row2017-12-18T00:00:00.000
ValueCountFrequency (%)
2017-08-29t00:00:00.000 3
 
5.0%
2017-09-11t00:00:00.000 3
 
5.0%
2017-12-14t00:00:00.000 3
 
5.0%
2017-10-12t00:00:00.000 2
 
3.3%
2017-08-02t00:00:00.000 2
 
3.3%
2017-09-21t00:00:00.000 2
 
3.3%
2017-07-12t00:00:00.000 2
 
3.3%
2017-12-18t00:00:00.000 2
 
3.3%
2016-10-04t00:00:00.000 2
 
3.3%
2015-07-02t00:00:00.000 2
 
3.3%
Other values (37) 37
61.7%
2023-12-09T23:28:06.352985image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 663
48.0%
1 128
 
9.3%
- 120
 
8.7%
: 120
 
8.7%
2 101
 
7.3%
T 60
 
4.3%
. 60
 
4.3%
7 53
 
3.8%
8 20
 
1.4%
9 14
 
1.0%
Other values (4) 41
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1020
73.9%
Other Punctuation 180
 
13.0%
Dash Punctuation 120
 
8.7%
Uppercase Letter 60
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 663
65.0%
1 128
 
12.5%
2 101
 
9.9%
7 53
 
5.2%
8 20
 
2.0%
9 14
 
1.4%
6 11
 
1.1%
4 10
 
1.0%
5 10
 
1.0%
3 10
 
1.0%
Other Punctuation
ValueCountFrequency (%)
: 120
66.7%
. 60
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 120
100.0%
Uppercase Letter
ValueCountFrequency (%)
T 60
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1320
95.7%
Latin 60
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 663
50.2%
1 128
 
9.7%
- 120
 
9.1%
: 120
 
9.1%
2 101
 
7.7%
. 60
 
4.5%
7 53
 
4.0%
8 20
 
1.5%
9 14
 
1.1%
6 11
 
0.8%
Other values (3) 30
 
2.3%
Latin
ValueCountFrequency (%)
T 60
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1380
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 663
48.0%
1 128
 
9.3%
- 120
 
8.7%
: 120
 
8.7%
2 101
 
7.3%
T 60
 
4.3%
. 60
 
4.3%
7 53
 
3.8%
8 20
 
1.4%
9 14
 
1.0%
Other values (4) 41
 
3.0%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size57.9 KiB
2023-12-09T23:28:06.490436image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.187
Min length2

Characters and Unicode

Total characters2187
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowYes
2nd rowNo
3rd rowNo
4th rowYes
5th rowNo
ValueCountFrequency (%)
no 813
81.3%
yes 187
 
18.7%
2023-12-09T23:28:06.721614image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 813
37.2%
o 813
37.2%
Y 187
 
8.6%
e 187
 
8.6%
s 187
 
8.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1187
54.3%
Uppercase Letter 1000
45.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 813
68.5%
e 187
 
15.8%
s 187
 
15.8%
Uppercase Letter
ValueCountFrequency (%)
N 813
81.3%
Y 187
 
18.7%

Most occurring scripts

ValueCountFrequency (%)
Latin 2187
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 813
37.2%
o 813
37.2%
Y 187
 
8.6%
e 187
 
8.6%
s 187
 
8.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2187
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 813
37.2%
o 813
37.2%
Y 187
 
8.6%
e 187
 
8.6%
s 187
 
8.6%

site_eui_kbtu_ft
Text

MISSING 

Distinct609
Distinct (%)67.6%
Missing99
Missing (%)9.9%
Memory size56.9 KiB
2023-12-09T23:28:07.219554image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length4
Mean length4.048834628
Min length1

Characters and Unicode

Total characters3648
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique404 ?
Unique (%)44.8%

Sample

1st row53.8
2nd row32
3rd row28.4
4th row130.2
5th row76.5
ValueCountFrequency (%)
106.8 7
 
0.8%
76.9 6
 
0.7%
91.9 5
 
0.6%
71.8 5
 
0.6%
63.8 5
 
0.6%
4.1 4
 
0.4%
43.3 4
 
0.4%
92.1 4
 
0.4%
73.5 4
 
0.4%
72.4 4
 
0.4%
Other values (599) 853
94.7%
2023-12-09T23:28:07.856920image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 816
22.4%
1 473
13.0%
8 321
 
8.8%
6 310
 
8.5%
7 290
 
7.9%
2 274
 
7.5%
4 258
 
7.1%
9 256
 
7.0%
5 253
 
6.9%
3 236
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2832
77.6%
Other Punctuation 816
 
22.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 473
16.7%
8 321
11.3%
6 310
10.9%
7 290
10.2%
2 274
9.7%
4 258
9.1%
9 256
9.0%
5 253
8.9%
3 236
8.3%
0 161
 
5.7%
Other Punctuation
ValueCountFrequency (%)
. 816
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3648
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 816
22.4%
1 473
13.0%
8 321
 
8.8%
6 310
 
8.5%
7 290
 
7.9%
2 274
 
7.5%
4 258
 
7.1%
9 256
 
7.0%
5 253
 
6.9%
3 236
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3648
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 816
22.4%
1 473
13.0%
8 321
 
8.8%
6 310
 
8.5%
7 290
 
7.9%
2 274
 
7.5%
4 258
 
7.1%
9 256
 
7.0%
5 253
 
6.9%
3 236
 
6.5%
Distinct553
Distinct (%)72.2%
Missing234
Missing (%)23.4%
Memory size53.1 KiB
2023-12-09T23:28:08.377156image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length4
Mean length4.095300261
Min length1

Characters and Unicode

Total characters3137
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique402 ?
Unique (%)52.5%

Sample

1st row56.2
2nd row31.3
3rd row133.7
4th row80.8
5th row20.5
ValueCountFrequency (%)
125.7 5
 
0.7%
91.8 5
 
0.7%
92.2 4
 
0.5%
93.2 4
 
0.5%
61.5 4
 
0.5%
83.5 4
 
0.5%
91.9 4
 
0.5%
76.1 4
 
0.5%
64.2 4
 
0.5%
28.3 4
 
0.5%
Other values (543) 724
94.5%
2023-12-09T23:28:09.012271image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 696
22.2%
1 435
13.9%
9 269
 
8.6%
7 258
 
8.2%
2 256
 
8.2%
8 243
 
7.7%
6 235
 
7.5%
3 215
 
6.9%
5 214
 
6.8%
4 178
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2441
77.8%
Other Punctuation 696
 
22.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 435
17.8%
9 269
11.0%
7 258
10.6%
2 256
10.5%
8 243
10.0%
6 235
9.6%
3 215
8.8%
5 214
8.8%
4 178
7.3%
0 138
 
5.7%
Other Punctuation
ValueCountFrequency (%)
. 696
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3137
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 696
22.2%
1 435
13.9%
9 269
 
8.6%
7 258
 
8.2%
2 256
 
8.2%
8 243
 
7.7%
6 235
 
7.5%
3 215
 
6.9%
5 214
 
6.8%
4 178
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3137
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 696
22.2%
1 435
13.9%
9 269
 
8.6%
7 258
 
8.2%
2 256
 
8.2%
8 243
 
7.7%
6 235
 
7.5%
3 215
 
6.9%
5 214
 
6.8%
4 178
 
5.7%
Distinct563
Distinct (%)57.5%
Missing21
Missing (%)2.1%
Memory size59.3 KiB
2023-12-09T23:28:09.510168image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.172625128
Min length2

Characters and Unicode

Total characters4085
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique345 ?
Unique (%)35.2%

Sample

1st row98.5
2nd row22.7
3rd row94.9
4th row186.7
5th row62.1
ValueCountFrequency (%)
59.6 40
 
4.1%
125.7 13
 
1.3%
67.3 10
 
1.0%
83.6 7
 
0.7%
106.2 7
 
0.7%
96.1 6
 
0.6%
28.5 5
 
0.5%
118.2 5
 
0.5%
68.2 5
 
0.5%
124.6 5
 
0.5%
Other values (553) 876
89.5%
2023-12-09T23:28:10.155145image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 893
21.9%
1 588
14.4%
9 349
 
8.5%
8 345
 
8.4%
6 328
 
8.0%
7 325
 
8.0%
2 295
 
7.2%
5 261
 
6.4%
4 243
 
5.9%
3 241
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3192
78.1%
Other Punctuation 893
 
21.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 588
18.4%
9 349
10.9%
8 345
10.8%
6 328
10.3%
7 325
10.2%
2 295
9.2%
5 261
8.2%
4 243
7.6%
3 241
7.6%
0 217
 
6.8%
Other Punctuation
ValueCountFrequency (%)
. 893
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4085
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 893
21.9%
1 588
14.4%
9 349
 
8.5%
8 345
 
8.4%
6 328
 
8.0%
7 325
 
8.0%
2 295
 
7.2%
5 261
 
6.4%
4 243
 
5.9%
3 241
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4085
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 893
21.9%
1 588
14.4%
9 349
 
8.5%
8 345
 
8.4%
6 328
 
8.0%
7 325
 
8.0%
2 295
 
7.2%
5 261
 
6.4%
4 243
 
5.9%
3 241
 
5.9%
Distinct617
Distinct (%)69.5%
Missing112
Missing (%)11.2%
Memory size56.8 KiB
2023-12-09T23:28:10.675981image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length5
Mean length4.337837838
Min length1

Characters and Unicode

Total characters3852
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique426 ?
Unique (%)48.0%

Sample

1st row-45.3
2nd row41.1
3rd row-70
4th row-30.3
5th row23.3
ValueCountFrequency (%)
0.2 9
 
1.0%
6 6
 
0.7%
35.4 6
 
0.7%
13.5 5
 
0.6%
2.8 5
 
0.6%
19.6 5
 
0.6%
21.3 5
 
0.6%
16.9 5
 
0.6%
33.8 5
 
0.6%
24.1 4
 
0.5%
Other values (512) 833
93.8%
2023-12-09T23:28:11.304576image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 801
20.8%
- 584
15.2%
2 351
9.1%
1 349
9.1%
3 336
8.7%
4 281
 
7.3%
5 273
 
7.1%
6 224
 
5.8%
7 196
 
5.1%
8 177
 
4.6%
Other values (2) 280
 
7.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2467
64.0%
Other Punctuation 801
 
20.8%
Dash Punctuation 584
 
15.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 351
14.2%
1 349
14.1%
3 336
13.6%
4 281
11.4%
5 273
11.1%
6 224
9.1%
7 196
7.9%
8 177
7.2%
9 175
7.1%
0 105
 
4.3%
Other Punctuation
ValueCountFrequency (%)
. 801
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 584
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3852
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 801
20.8%
- 584
15.2%
2 351
9.1%
1 349
9.1%
3 336
8.7%
4 281
 
7.3%
5 273
 
7.1%
6 224
 
5.8%
7 196
 
5.1%
8 177
 
4.6%
Other values (2) 280
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3852
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 801
20.8%
- 584
15.2%
2 351
9.1%
1 349
9.1%
3 336
8.7%
4 281
 
7.3%
5 273
 
7.1%
6 224
 
5.8%
7 196
 
5.1%
8 177
 
4.6%
Other values (2) 280
 
7.3%

site_energy_use_kbtu
Text

MISSING 

Distinct809
Distinct (%)89.8%
Missing99
Missing (%)9.9%
Memory size61.3 KiB
2023-12-09T23:28:11.653325image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length11
Median length9
Mean length9.045504994
Min length1

Characters and Unicode

Total characters8150
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique729 ?
Unique (%)80.9%

Sample

1st row9120623.9
2nd row3337870.1
3rd row2684643.8
4th row16279359.5
5th row3825211.3
ValueCountFrequency (%)
6672006.3 5
 
0.6%
3440512.5 4
 
0.4%
202800 3
 
0.3%
991999.9 3
 
0.3%
3144282.1 3
 
0.3%
2955322 3
 
0.3%
3636452.3 3
 
0.3%
9860563.8 3
 
0.3%
83219364.2 3
 
0.3%
42088.7 2
 
0.2%
Other values (799) 869
96.4%
2023-12-09T23:28:12.115420image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 825
10.1%
1 800
9.8%
. 797
9.8%
2 785
9.6%
4 776
9.5%
5 764
9.4%
6 758
9.3%
9 700
8.6%
8 685
8.4%
7 675
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7353
90.2%
Other Punctuation 797
 
9.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 825
11.2%
1 800
10.9%
2 785
10.7%
4 776
10.6%
5 764
10.4%
6 758
10.3%
9 700
9.5%
8 685
9.3%
7 675
9.2%
0 585
8.0%
Other Punctuation
ValueCountFrequency (%)
. 797
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8150
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 825
10.1%
1 800
9.8%
. 797
9.8%
2 785
9.6%
4 776
9.5%
5 764
9.4%
6 758
9.3%
9 700
8.6%
8 685
8.4%
7 675
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8150
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 825
10.1%
1 800
9.8%
. 797
9.8%
2 785
9.6%
4 776
9.5%
5 764
9.4%
6 758
9.3%
9 700
8.6%
8 685
8.4%
7 675
8.3%
Distinct700
Distinct (%)91.4%
Missing234
Missing (%)23.4%
Memory size56.9 KiB
2023-12-09T23:28:12.435619image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length11
Median length9
Mean length9.135770235
Min length1

Characters and Unicode

Total characters6998
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique644 ?
Unique (%)84.1%

Sample

1st row9515719.3
2nd row2952627
3rd row16711605
4th row4039630.6
5th row1022951.6
ValueCountFrequency (%)
7032320.6 5
 
0.7%
3401633.4 4
 
0.5%
2922340.7 3
 
0.4%
3591374.9 3
 
0.4%
88122389.2 3
 
0.4%
10470136.2 3
 
0.4%
3196396.2 3
 
0.4%
9120620.8 2
 
0.3%
36098645.5 2
 
0.3%
64818295.1 2
 
0.3%
Other values (690) 736
96.1%
2023-12-09T23:28:12.871761image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 747
10.7%
3 742
10.6%
. 685
9.8%
2 653
9.3%
5 621
8.9%
6 617
8.8%
4 612
8.7%
7 608
8.7%
9 592
8.5%
8 582
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6313
90.2%
Other Punctuation 685
 
9.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 747
11.8%
3 742
11.8%
2 653
10.3%
5 621
9.8%
6 617
9.8%
4 612
9.7%
7 608
9.6%
9 592
9.4%
8 582
9.2%
0 539
8.5%
Other Punctuation
ValueCountFrequency (%)
. 685
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6998
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 747
10.7%
3 742
10.6%
. 685
9.8%
2 653
9.3%
5 621
8.9%
6 617
8.8%
4 612
8.7%
7 608
8.7%
9 592
8.5%
8 582
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6998
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 747
10.7%
3 742
10.6%
. 685
9.8%
2 653
9.3%
5 621
8.9%
6 617
8.8%
4 612
8.7%
7 608
8.7%
9 592
8.5%
8 582
8.3%
Distinct896
Distinct (%)91.5%
Missing21
Missing (%)2.1%
Memory size64.1 KiB
2023-12-09T23:28:13.212348image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length11
Median length9
Mean length9.202247191
Min length7

Characters and Unicode

Total characters9009
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique824 ?
Unique (%)84.2%

Sample

1st row16687684
2nd row2365579.9
3rd row8953801.2
4th row23341741.6
5th row3102538.4
ValueCountFrequency (%)
8109106.7 4
 
0.4%
8942751.7 3
 
0.3%
144376363.7 3
 
0.3%
3345095.1 3
 
0.3%
5728500.6 3
 
0.3%
6682456.7 3
 
0.3%
4587306.2 3
 
0.3%
9843143.6 3
 
0.3%
6247875.2 3
 
0.3%
6816747.8 3
 
0.3%
Other values (886) 948
96.8%
2023-12-09T23:28:13.695934image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 960
10.7%
5 898
10.0%
2 896
9.9%
. 890
9.9%
3 835
9.3%
7 806
8.9%
6 805
8.9%
8 776
8.6%
4 762
8.5%
9 740
8.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8119
90.1%
Other Punctuation 890
 
9.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 960
11.8%
5 898
11.1%
2 896
11.0%
3 835
10.3%
7 806
9.9%
6 805
9.9%
8 776
9.6%
4 762
9.4%
9 740
9.1%
0 641
7.9%
Other Punctuation
ValueCountFrequency (%)
. 890
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9009
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 960
10.7%
5 898
10.0%
2 896
9.9%
. 890
9.9%
3 835
9.3%
7 806
8.9%
6 805
8.9%
8 776
8.6%
4 762
8.5%
9 740
8.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9009
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 960
10.7%
5 898
10.0%
2 896
9.9%
. 890
9.9%
3 835
9.3%
7 806
8.9%
6 805
8.9%
8 776
8.6%
4 762
8.5%
9 740
8.2%
Distinct230
Distinct (%)27.7%
Missing170
Missing (%)17.0%
Memory size54.2 KiB
2023-12-09T23:28:14.209315image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.143373494
Min length1

Characters and Unicode

Total characters2609
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique77 ?
Unique (%)9.3%

Sample

1st row11.3
2nd row7.1
3rd row2
4th row18.8
5th row11.7
ValueCountFrequency (%)
3.9 19
 
2.3%
3.5 16
 
1.9%
3.4 15
 
1.8%
3.7 15
 
1.8%
5.3 14
 
1.7%
4 14
 
1.7%
4.7 13
 
1.6%
0.8 13
 
1.6%
4.1 13
 
1.6%
4.8 12
 
1.4%
Other values (220) 686
82.7%
2023-12-09T23:28:14.839842image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 751
28.8%
1 365
14.0%
3 242
 
9.3%
2 213
 
8.2%
4 200
 
7.7%
5 164
 
6.3%
7 160
 
6.1%
8 145
 
5.6%
6 141
 
5.4%
9 127
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1858
71.2%
Other Punctuation 751
28.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 365
19.6%
3 242
13.0%
2 213
11.5%
4 200
10.8%
5 164
8.8%
7 160
8.6%
8 145
 
7.8%
6 141
 
7.6%
9 127
 
6.8%
0 101
 
5.4%
Other Punctuation
ValueCountFrequency (%)
. 751
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2609
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 751
28.8%
1 365
14.0%
3 242
 
9.3%
2 213
 
8.2%
4 200
 
7.7%
5 164
 
6.3%
7 160
 
6.1%
8 145
 
5.6%
6 141
 
5.4%
9 127
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2609
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 751
28.8%
1 365
14.0%
3 242
 
9.3%
2 213
 
8.2%
4 200
 
7.7%
5 164
 
6.3%
7 160
 
6.1%
8 145
 
5.6%
6 141
 
5.4%
9 127
 
4.9%
Distinct27
Distinct (%)3.8%
Missing284
Missing (%)28.4%
Memory size50.6 KiB
2023-12-09T23:28:15.032727image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.446927374
Min length1

Characters and Unicode

Total characters1752
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)0.7%

Sample

1st row0.1
2nd row0.2
3rd row0.7
4th row0.4
5th row0.1
ValueCountFrequency (%)
0 173
24.2%
0.1 79
11.0%
0.8 68
 
9.5%
0.6 59
 
8.2%
0.7 58
 
8.1%
0.2 43
 
6.0%
0.3 42
 
5.9%
0.9 41
 
5.7%
0.4 37
 
5.2%
0.5 35
 
4.9%
Other values (17) 81
11.3%
2023-12-09T23:28:15.349076image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 635
36.2%
. 518
29.6%
1 173
 
9.9%
8 70
 
4.0%
6 64
 
3.7%
7 59
 
3.4%
2 58
 
3.3%
3 48
 
2.7%
4 45
 
2.6%
9 43
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1234
70.4%
Other Punctuation 518
29.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 635
51.5%
1 173
 
14.0%
8 70
 
5.7%
6 64
 
5.2%
7 59
 
4.8%
2 58
 
4.7%
3 48
 
3.9%
4 45
 
3.6%
9 43
 
3.5%
5 39
 
3.2%
Other Punctuation
ValueCountFrequency (%)
. 518
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1752
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 635
36.2%
. 518
29.6%
1 173
 
9.9%
8 70
 
4.0%
6 64
 
3.7%
7 59
 
3.4%
2 58
 
3.3%
3 48
 
2.7%
4 45
 
2.6%
9 43
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1752
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 635
36.2%
. 518
29.6%
1 173
 
9.9%
8 70
 
4.0%
6 64
 
3.7%
7 59
 
3.4%
2 58
 
3.3%
3 48
 
2.7%
4 45
 
2.6%
9 43
 
2.5%

source_eui_kbtu_ft
Text

MISSING 

Distinct689
Distinct (%)76.5%
Missing99
Missing (%)9.9%
Memory size57.3 KiB
2023-12-09T23:28:15.814790image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length8
Median length5
Mean length4.506104329
Min length1

Characters and Unicode

Total characters4060
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique530 ?
Unique (%)58.8%

Sample

1st row138.4
2nd row84.6
3rd row43.5
4th row271.1
5th row163
ValueCountFrequency (%)
105.9 5
 
0.6%
135.9 5
 
0.6%
119.1 4
 
0.4%
127.4 4
 
0.4%
93.8 4
 
0.4%
84.6 4
 
0.4%
89.9 4
 
0.4%
80.1 4
 
0.4%
126.3 4
 
0.4%
99.6 3
 
0.3%
Other values (679) 860
95.4%
2023-12-09T23:28:16.416599image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 811
20.0%
1 752
18.5%
2 360
8.9%
3 321
 
7.9%
4 300
 
7.4%
9 295
 
7.3%
8 289
 
7.1%
6 285
 
7.0%
5 240
 
5.9%
7 225
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3249
80.0%
Other Punctuation 811
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 752
23.1%
2 360
11.1%
3 321
9.9%
4 300
 
9.2%
9 295
 
9.1%
8 289
 
8.9%
6 285
 
8.8%
5 240
 
7.4%
7 225
 
6.9%
0 182
 
5.6%
Other Punctuation
ValueCountFrequency (%)
. 811
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4060
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 811
20.0%
1 752
18.5%
2 360
8.9%
3 321
 
7.9%
4 300
 
7.4%
9 295
 
7.3%
8 289
 
7.1%
6 285
 
7.0%
5 240
 
5.9%
7 225
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4060
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 811
20.0%
1 752
18.5%
2 360
8.9%
3 321
 
7.9%
4 300
 
7.4%
9 295
 
7.3%
8 289
 
7.1%
6 285
 
7.0%
5 240
 
5.9%
7 225
 
5.5%
Distinct608
Distinct (%)79.4%
Missing234
Missing (%)23.4%
Memory size53.5 KiB
2023-12-09T23:28:16.929420image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length8
Median length5
Mean length4.593994778
Min length1

Characters and Unicode

Total characters3519
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique476 ?
Unique (%)62.1%

Sample

1st row141
2nd row46.8
3rd row274.7
4th row167.9
5th row64.2
ValueCountFrequency (%)
88.9 5
 
0.7%
112.6 4
 
0.5%
105.2 4
 
0.5%
104.3 4
 
0.5%
112.4 3
 
0.4%
151 3
 
0.4%
189.6 3
 
0.4%
222.8 3
 
0.4%
201.1 3
 
0.4%
271.6 3
 
0.4%
Other values (598) 731
95.4%
2023-12-09T23:28:17.628856image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 701
19.9%
1 663
18.8%
2 375
10.7%
3 264
 
7.5%
8 247
 
7.0%
4 229
 
6.5%
7 228
 
6.5%
5 219
 
6.2%
9 217
 
6.2%
6 214
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2818
80.1%
Other Punctuation 701
 
19.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 663
23.5%
2 375
13.3%
3 264
 
9.4%
8 247
 
8.8%
4 229
 
8.1%
7 228
 
8.1%
5 219
 
7.8%
9 217
 
7.7%
6 214
 
7.6%
0 162
 
5.7%
Other Punctuation
ValueCountFrequency (%)
. 701
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3519
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 701
19.9%
1 663
18.8%
2 375
10.7%
3 264
 
7.5%
8 247
 
7.0%
4 229
 
6.5%
7 228
 
6.5%
5 219
 
6.2%
9 217
 
6.2%
6 214
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3519
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 701
19.9%
1 663
18.8%
2 375
10.7%
3 264
 
7.5%
8 247
 
7.0%
4 229
 
6.5%
7 228
 
6.5%
5 219
 
6.2%
9 217
 
6.2%
6 214
 
6.1%
Distinct492
Distinct (%)50.3%
Missing21
Missing (%)2.1%
Memory size59.9 KiB
2023-12-09T23:28:18.058683image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.792645557
Min length2

Characters and Unicode

Total characters4692
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique357 ?
Unique (%)36.5%

Sample

1st row253.2
2nd row60
3rd row145.1
4th row388.7
5th row132.2
ValueCountFrequency (%)
127.9 109
 
11.1%
115.1 52
 
5.3%
123.1 42
 
4.3%
262.6 21
 
2.1%
148.1 17
 
1.7%
243.2 13
 
1.3%
47.6 11
 
1.1%
85.1 10
 
1.0%
141.4 9
 
0.9%
60 8
 
0.8%
Other values (482) 687
70.2%
2023-12-09T23:28:18.944104image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1114
23.7%
. 907
19.3%
2 663
14.1%
7 324
 
6.9%
3 314
 
6.7%
4 275
 
5.9%
9 271
 
5.8%
5 271
 
5.8%
6 237
 
5.1%
8 204
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3785
80.7%
Other Punctuation 907
 
19.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1114
29.4%
2 663
17.5%
7 324
 
8.6%
3 314
 
8.3%
4 275
 
7.3%
9 271
 
7.2%
5 271
 
7.2%
6 237
 
6.3%
8 204
 
5.4%
0 112
 
3.0%
Other Punctuation
ValueCountFrequency (%)
. 907
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4692
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1114
23.7%
. 907
19.3%
2 663
14.1%
7 324
 
6.9%
3 314
 
6.7%
4 275
 
5.9%
9 271
 
5.8%
5 271
 
5.8%
6 237
 
5.1%
8 204
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4692
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1114
23.7%
. 907
19.3%
2 663
14.1%
7 324
 
6.9%
3 314
 
6.7%
4 275
 
5.9%
9 271
 
5.8%
5 271
 
5.8%
6 237
 
5.1%
8 204
 
4.3%
Distinct617
Distinct (%)69.5%
Missing112
Missing (%)11.2%
Memory size56.8 KiB
2023-12-09T23:28:19.788227image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length5
Mean length4.337837838
Min length1

Characters and Unicode

Total characters3852
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique426 ?
Unique (%)48.0%

Sample

1st row-45.3
2nd row41.1
3rd row-70
4th row-30.3
5th row23.3
ValueCountFrequency (%)
0.2 9
 
1.0%
6 6
 
0.7%
35.4 6
 
0.7%
13.5 5
 
0.6%
2.8 5
 
0.6%
19.6 5
 
0.6%
21.3 5
 
0.6%
16.9 5
 
0.6%
33.8 5
 
0.6%
24.1 4
 
0.5%
Other values (512) 833
93.8%
2023-12-09T23:28:20.964777image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 801
20.8%
- 584
15.2%
2 351
9.1%
1 349
9.1%
3 336
8.7%
4 281
 
7.3%
5 273
 
7.1%
6 224
 
5.8%
7 196
 
5.1%
8 177
 
4.6%
Other values (2) 280
 
7.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2467
64.0%
Other Punctuation 801
 
20.8%
Dash Punctuation 584
 
15.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 351
14.2%
1 349
14.1%
3 336
13.6%
4 281
11.4%
5 273
11.1%
6 224
9.1%
7 196
7.9%
8 177
7.2%
9 175
7.1%
0 105
 
4.3%
Other Punctuation
ValueCountFrequency (%)
. 801
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 584
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3852
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 801
20.8%
- 584
15.2%
2 351
9.1%
1 349
9.1%
3 336
8.7%
4 281
 
7.3%
5 273
 
7.1%
6 224
 
5.8%
7 196
 
5.1%
8 177
 
4.6%
Other values (2) 280
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3852
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 801
20.8%
- 584
15.2%
2 351
9.1%
1 349
9.1%
3 336
8.7%
4 281
 
7.3%
5 273
 
7.1%
6 224
 
5.8%
7 196
 
5.1%
8 177
 
4.6%
Other values (2) 280
 
7.3%
Distinct628
Distinct (%)90.2%
Missing304
Missing (%)30.4%
Memory size54.8 KiB
2023-12-09T23:28:21.538598image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length11
Median length10
Mean length9.402298851
Min length6

Characters and Unicode

Total characters6544
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique569 ?
Unique (%)81.8%

Sample

1st row23442537.1
2nd row4107034.4
3rd row33884208.5
4th row8147757.9
5th row3212068.1
ValueCountFrequency (%)
10803209.4 4
 
0.6%
11706536.6 4
 
0.6%
212940 3
 
0.4%
170180909.2 3
 
0.4%
1041599.9 3
 
0.4%
11418460.3 3
 
0.4%
7262037.6 3
 
0.4%
7482261.3 2
 
0.3%
58193475.7 2
 
0.3%
80847062.3 2
 
0.3%
Other values (618) 667
95.8%
2023-12-09T23:28:22.054700image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 744
11.4%
3 637
9.7%
. 626
9.6%
4 604
9.2%
2 599
9.2%
5 593
9.1%
9 565
8.6%
7 562
8.6%
6 559
8.5%
8 558
8.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5918
90.4%
Other Punctuation 626
 
9.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 744
12.6%
3 637
10.8%
4 604
10.2%
2 599
10.1%
5 593
10.0%
9 565
9.5%
7 562
9.5%
6 559
9.4%
8 558
9.4%
0 497
8.4%
Other Punctuation
ValueCountFrequency (%)
. 626
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6544
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 744
11.4%
3 637
9.7%
. 626
9.6%
4 604
9.2%
2 599
9.2%
5 593
9.1%
9 565
8.6%
7 562
8.6%
6 559
8.5%
8 558
8.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6544
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 744
11.4%
3 637
9.7%
. 626
9.6%
4 604
9.2%
2 599
9.2%
5 593
9.1%
9 565
8.6%
7 562
8.6%
6 559
8.5%
8 558
8.5%
Distinct810
Distinct (%)89.9%
Missing99
Missing (%)9.9%
Memory size61.6 KiB
2023-12-09T23:28:22.382262image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length11
Median length10
Mean length9.381798002
Min length1

Characters and Unicode

Total characters8453
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique731 ?
Unique (%)81.1%

Sample

1st row23442537.1
2nd row8833819.4
3rd row4107034.4
4th row33884208.5
5th row8147757.9
ValueCountFrequency (%)
11706536.6 5
 
0.6%
10803209.4 4
 
0.4%
21903779.6 3
 
0.3%
9873045.6 3
 
0.3%
7262037.6 3
 
0.3%
170180909.2 3
 
0.3%
1041599.9 3
 
0.3%
11418460.3 3
 
0.3%
212940 3
 
0.3%
20357284.4 2
 
0.2%
Other values (800) 869
96.4%
2023-12-09T23:28:22.830272image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 954
11.3%
3 823
9.7%
. 813
9.6%
4 790
9.3%
2 762
9.0%
5 756
8.9%
8 738
8.7%
7 730
8.6%
6 723
8.6%
9 713
8.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7640
90.4%
Other Punctuation 813
 
9.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 954
12.5%
3 823
10.8%
4 790
10.3%
2 762
10.0%
5 756
9.9%
8 738
9.7%
7 730
9.6%
6 723
9.5%
9 713
9.3%
0 651
8.5%
Other Punctuation
ValueCountFrequency (%)
. 813
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8453
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 954
11.3%
3 823
9.7%
. 813
9.6%
4 790
9.3%
2 762
9.0%
5 756
8.9%
8 738
8.7%
7 730
8.6%
6 723
8.6%
9 713
8.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8453
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 954
11.3%
3 823
9.7%
. 813
9.6%
4 790
9.3%
2 762
9.0%
5 756
8.9%
8 738
8.7%
7 730
8.6%
6 723
8.6%
9 713
8.4%
Distinct700
Distinct (%)91.4%
Missing234
Missing (%)23.4%
Memory size57.1 KiB
2023-12-09T23:28:23.598190image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length11
Median length10
Mean length9.421671018
Min length1

Characters and Unicode

Total characters7217
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique644 ?
Unique (%)84.1%

Sample

1st row23882428.7
2nd row4413318
3rd row34338066.2
4th row8395581.5
5th row3212068.1
ValueCountFrequency (%)
12023580.9 5
 
0.7%
10681128.8 4
 
0.5%
22616330.3 3
 
0.4%
7158476.4 3
 
0.4%
174939096.5 3
 
0.4%
11276917.2 3
 
0.4%
10036684 3
 
0.4%
19135180.2 2
 
0.3%
5334512.5 2
 
0.3%
4612513.9 2
 
0.3%
Other values (690) 736
96.1%
2023-12-09T23:28:24.074120image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 872
12.1%
2 700
9.7%
. 675
9.4%
5 659
9.1%
8 654
9.1%
3 653
9.0%
4 642
8.9%
6 637
8.8%
7 614
8.5%
9 589
8.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6542
90.6%
Other Punctuation 675
 
9.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 872
13.3%
2 700
10.7%
5 659
10.1%
8 654
10.0%
3 653
10.0%
4 642
9.8%
6 637
9.7%
7 614
9.4%
9 589
9.0%
0 522
8.0%
Other Punctuation
ValueCountFrequency (%)
. 675
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7217
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 872
12.1%
2 700
9.7%
. 675
9.4%
5 659
9.1%
8 654
9.1%
3 653
9.0%
4 642
8.9%
6 637
8.8%
7 614
8.5%
9 589
8.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7217
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 872
12.1%
2 700
9.7%
. 675
9.4%
5 659
9.1%
8 654
9.1%
3 653
9.0%
4 642
8.9%
6 637
8.8%
7 614
8.5%
9 589
8.2%
Distinct879
Distinct (%)89.8%
Missing21
Missing (%)2.1%
Memory size64.3 KiB
2023-12-09T23:28:24.408329image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length11
Median length10
Mean length9.427987743
Min length7

Characters and Unicode

Total characters9230
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique796 ?
Unique (%)81.3%

Sample

1st row42891984
2nd row6260610.6
3rd row13697745.6
4th row48584001.9
5th row6608454.2
ValueCountFrequency (%)
40401825.9 6
 
0.6%
25462598 4
 
0.4%
15352746 3
 
0.3%
4816671.3 3
 
0.3%
7157584.8 3
 
0.3%
295244987.5 3
 
0.3%
17987494 3
 
0.3%
19189528.2 3
 
0.3%
6555783.8 3
 
0.3%
21865081.3 3
 
0.3%
Other values (869) 945
96.5%
2023-12-09T23:28:24.871060image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1054
11.4%
2 898
9.7%
4 869
9.4%
5 858
9.3%
. 858
9.3%
3 838
9.1%
7 812
8.8%
8 807
8.7%
6 803
8.7%
9 769
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8372
90.7%
Other Punctuation 858
 
9.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1054
12.6%
2 898
10.7%
4 869
10.4%
5 858
10.2%
3 838
10.0%
7 812
9.7%
8 807
9.6%
6 803
9.6%
9 769
9.2%
0 664
7.9%
Other Punctuation
ValueCountFrequency (%)
. 858
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9230
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1054
11.4%
2 898
9.7%
4 869
9.4%
5 858
9.3%
. 858
9.3%
3 838
9.1%
7 812
8.8%
8 807
8.7%
6 803
8.7%
9 769
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9230
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1054
11.4%
2 898
9.7%
4 869
9.4%
5 858
9.3%
. 858
9.3%
3 838
9.1%
7 812
8.8%
8 807
8.7%
6 803
8.7%
9 769
8.3%

fuel_oil_1_use_kbtu
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1000
Missing (%)100.0%
Memory size7.9 KiB

fuel_oil_2_use_kbtu
Text

MISSING 

Distinct117
Distinct (%)74.5%
Missing843
Missing (%)84.3%
Memory size36.3 KiB
2023-12-09T23:28:25.243922image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length10
Median length9
Mean length6.993630573
Min length1

Characters and Unicode

Total characters1098
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)62.4%

Sample

1st row773283
2nd row0
3rd row669700.6
4th row2559996.7
5th row1123872.1
ValueCountFrequency (%)
0 20
 
12.7%
414000 4
 
2.5%
138000 3
 
1.9%
21868033.8 2
 
1.3%
483000.2 2
 
1.3%
1123872.1 2
 
1.3%
5208313.6 2
 
1.3%
773283 2
 
1.3%
358179 2
 
1.3%
906384 2
 
1.3%
Other values (107) 116
73.9%
2023-12-09T23:28:25.725954image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 153
13.9%
1 115
10.5%
8 110
10.0%
2 110
10.0%
9 94
8.6%
5 93
8.5%
4 91
8.3%
6 89
8.1%
3 84
7.7%
7 81
7.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1020
92.9%
Other Punctuation 78
 
7.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 153
15.0%
1 115
11.3%
8 110
10.8%
2 110
10.8%
9 94
9.2%
5 93
9.1%
4 91
8.9%
6 89
8.7%
3 84
8.2%
7 81
7.9%
Other Punctuation
ValueCountFrequency (%)
. 78
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1098
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 153
13.9%
1 115
10.5%
8 110
10.0%
2 110
10.0%
9 94
8.6%
5 93
8.5%
4 91
8.3%
6 89
8.1%
3 84
7.7%
7 81
7.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1098
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 153
13.9%
1 115
10.5%
8 110
10.0%
2 110
10.0%
9 94
8.6%
5 93
8.5%
4 91
8.3%
6 89
8.1%
3 84
7.7%
7 81
7.4%

fuel_oil_4_use_kbtu
Text

MISSING 

Distinct62
Distinct (%)88.6%
Missing930
Missing (%)93.0%
Memory size33.6 KiB
2023-12-09T23:28:26.023782image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length10
Median length9
Mean length8.171428571
Min length1

Characters and Unicode

Total characters572
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique57 ?
Unique (%)81.4%

Sample

1st row2092618
2nd row2095950.5
3rd row11569322.7
4th row3793518.4
5th row4296050
ValueCountFrequency (%)
0 5
 
7.1%
3793518.4 2
 
2.9%
6081483.8 2
 
2.9%
4599875.6 2
 
2.9%
4640575.2 2
 
2.9%
4552382.2 1
 
1.4%
5464634.3 1
 
1.4%
4708937.8 1
 
1.4%
3821654.3 1
 
1.4%
2120065.8 1
 
1.4%
Other values (52) 52
74.3%
2023-12-09T23:28:26.437067image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 61
10.7%
6 60
10.5%
0 54
9.4%
1 54
9.4%
3 53
9.3%
. 52
9.1%
2 52
9.1%
7 51
8.9%
5 49
8.6%
9 48
8.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 520
90.9%
Other Punctuation 52
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 61
11.7%
6 60
11.5%
0 54
10.4%
1 54
10.4%
3 53
10.2%
2 52
10.0%
7 51
9.8%
5 49
9.4%
9 48
9.2%
8 38
7.3%
Other Punctuation
ValueCountFrequency (%)
. 52
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 61
10.7%
6 60
10.5%
0 54
9.4%
1 54
9.4%
3 53
9.3%
. 52
9.1%
2 52
9.1%
7 51
8.9%
5 49
8.6%
9 48
8.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 61
10.7%
6 60
10.5%
0 54
9.4%
1 54
9.4%
3 53
9.3%
. 52
9.1%
2 52
9.1%
7 51
8.9%
5 49
8.6%
9 48
8.4%

fuel_oil_5_6_use_kbtu
Text

MISSING 

Distinct9
Distinct (%)75.0%
Missing988
Missing (%)98.8%
Memory size31.7 KiB
2023-12-09T23:28:26.628804image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length10
Median length9.5
Mean length6.75
Min length1

Characters and Unicode

Total characters81
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)58.3%

Sample

1st row0
2nd row156341.1
3rd row4962455.4
4th row0
5th row7330517.6
ValueCountFrequency (%)
0 3
25.0%
9782187.7 2
16.7%
156341.1 1
 
8.3%
3899549.9 1
 
8.3%
900000 1
 
8.3%
4127700.1 1
 
8.3%
7330517.6 1
 
8.3%
4962455.4 1
 
8.3%
49138799.2 1
 
8.3%
2023-12-09T23:28:26.928565image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
13.6%
9 11
13.6%
7 11
13.6%
1 9
11.1%
. 8
9.9%
4 7
8.6%
8 6
7.4%
2 5
6.2%
5 5
6.2%
3 5
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 73
90.1%
Other Punctuation 8
 
9.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
15.1%
9 11
15.1%
7 11
15.1%
1 9
12.3%
4 7
9.6%
8 6
8.2%
2 5
6.8%
5 5
6.8%
3 5
6.8%
6 3
 
4.1%
Other Punctuation
ValueCountFrequency (%)
. 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 81
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
13.6%
9 11
13.6%
7 11
13.6%
1 9
11.1%
. 8
9.9%
4 7
8.6%
8 6
7.4%
2 5
6.2%
5 5
6.2%
3 5
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 81
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
13.6%
9 11
13.6%
7 11
13.6%
1 9
11.1%
. 8
9.9%
4 7
8.6%
8 6
7.4%
2 5
6.2%
5 5
6.2%
3 5
6.2%

diesel_2_use_kbtu
Text

MISSING 

Distinct4
Distinct (%)100.0%
Missing996
Missing (%)99.6%
Memory size31.5 KiB
2023-12-09T23:28:27.094791image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length8
Median length7.5
Mean length5.75
Min length1

Characters and Unicode

Total characters23
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st row11380722
2nd row0
3rd row70393.8
4th row96627.6
ValueCountFrequency (%)
11380722 1
25.0%
70393.8 1
25.0%
96627.6 1
25.0%
0 1
25.0%
2023-12-09T23:28:27.385409image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 3
13.0%
0 3
13.0%
7 3
13.0%
2 3
13.0%
6 3
13.0%
1 2
8.7%
8 2
8.7%
9 2
8.7%
. 2
8.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 21
91.3%
Other Punctuation 2
 
8.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 3
14.3%
0 3
14.3%
7 3
14.3%
2 3
14.3%
6 3
14.3%
1 2
9.5%
8 2
9.5%
9 2
9.5%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 23
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 3
13.0%
0 3
13.0%
7 3
13.0%
2 3
13.0%
6 3
13.0%
1 2
8.7%
8 2
8.7%
9 2
8.7%
. 2
8.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 3
13.0%
0 3
13.0%
7 3
13.0%
2 3
13.0%
6 3
13.0%
1 2
8.7%
8 2
8.7%
9 2
8.7%
. 2
8.7%

kerosene_use_kbtu
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1000
Missing (%)100.0%
Memory size7.9 KiB

propane_use_kbtu
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1000
Missing (%)100.0%
Memory size7.9 KiB
Distinct117
Distinct (%)92.9%
Missing874
Missing (%)87.4%
Memory size35.6 KiB
2023-12-09T23:28:27.729838image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length11
Median length10
Mean length9.26984127
Min length5

Characters and Unicode

Total characters1168
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique110 ?
Unique (%)87.3%

Sample

1st row1133475.1
2nd row7195772.2
3rd row10443801.1
4th row3431667.1
5th row38591282.7
ValueCountFrequency (%)
4676604.5 3
 
2.4%
44716014.6 3
 
2.4%
8696315.5 2
 
1.6%
40817632 2
 
1.6%
79038099.3 2
 
1.6%
15105897.7 2
 
1.6%
8331887.2 2
 
1.6%
9663092.1 1
 
0.8%
9292723.1 1
 
0.8%
24323528.6 1
 
0.8%
Other values (107) 107
84.9%
2023-12-09T23:28:28.218147image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 137
11.7%
3 120
10.3%
4 113
9.7%
2 109
9.3%
5 107
9.2%
. 106
9.1%
6 101
8.6%
8 99
8.5%
9 98
8.4%
7 90
7.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1062
90.9%
Other Punctuation 106
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 137
12.9%
3 120
11.3%
4 113
10.6%
2 109
10.3%
5 107
10.1%
6 101
9.5%
8 99
9.3%
9 98
9.2%
7 90
8.5%
0 88
8.3%
Other Punctuation
ValueCountFrequency (%)
. 106
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1168
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 137
11.7%
3 120
10.3%
4 113
9.7%
2 109
9.3%
5 107
9.2%
. 106
9.1%
6 101
8.6%
8 99
8.5%
9 98
8.4%
7 90
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1168
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 137
11.7%
3 120
10.3%
4 113
9.7%
2 109
9.3%
5 107
9.2%
. 106
9.1%
6 101
8.6%
8 99
8.5%
9 98
8.4%
7 90
7.7%

district_hot_water_use_kbtu
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1000
Missing (%)100.0%
Memory size7.9 KiB

district_chilled_water_use
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing999
Missing (%)99.9%
Memory size31.4 KiB
2023-12-09T23:28:28.390217image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters10
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row61511338.5
ValueCountFrequency (%)
61511338.5 1
100.0%
2023-12-09T23:28:28.656886image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 3
30.0%
5 2
20.0%
3 2
20.0%
6 1
 
10.0%
8 1
 
10.0%
. 1
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9
90.0%
Other Punctuation 1
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3
33.3%
5 2
22.2%
3 2
22.2%
6 1
 
11.1%
8 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 3
30.0%
5 2
20.0%
3 2
20.0%
6 1
 
10.0%
8 1
 
10.0%
. 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3
30.0%
5 2
20.0%
3 2
20.0%
6 1
 
10.0%
8 1
 
10.0%
. 1
 
10.0%

natural_gas_use_kbtu
Text

MISSING 

Distinct692
Distinct (%)89.5%
Missing227
Missing (%)22.7%
Memory size56.5 KiB
2023-12-09T23:28:28.963166image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length11
Median length9
Mean length8.298835705
Min length1

Characters and Unicode

Total characters6415
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique621 ?
Unique (%)80.3%

Sample

1st row1435754.7
2nd row2068300.1
3rd row8245445.1
4th row1848519.4
5th row1902140
ValueCountFrequency (%)
4422757.5 5
 
0.6%
0 4
 
0.5%
513583.3 3
 
0.4%
965394 3
 
0.4%
2160197 3
 
0.4%
202800 3
 
0.4%
991999.9 3
 
0.4%
1813470.3 2
 
0.3%
8294332 2
 
0.3%
4414844.8 2
 
0.3%
Other values (682) 743
96.1%
2023-12-09T23:28:29.397696image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 690
10.8%
1 677
10.6%
. 635
9.9%
2 605
9.4%
0 599
9.3%
6 575
9.0%
4 573
8.9%
9 571
8.9%
8 514
8.0%
5 506
7.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5780
90.1%
Other Punctuation 635
 
9.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 690
11.9%
1 677
11.7%
2 605
10.5%
0 599
10.4%
6 575
9.9%
4 573
9.9%
9 571
9.9%
8 514
8.9%
5 506
8.8%
7 470
8.1%
Other Punctuation
ValueCountFrequency (%)
. 635
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6415
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 690
10.8%
1 677
10.6%
. 635
9.9%
2 605
9.4%
0 599
9.3%
6 575
9.0%
4 573
8.9%
9 571
8.9%
8 514
8.0%
5 506
7.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6415
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 690
10.8%
1 677
10.6%
. 635
9.9%
2 605
9.4%
0 599
9.3%
6 575
9.0%
4 573
8.9%
9 571
8.9%
8 514
8.0%
5 506
7.9%
Distinct650
Distinct (%)90.8%
Missing284
Missing (%)28.4%
Memory size53.4 KiB
2023-12-09T23:28:29.799786image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length9
Median length7
Mean length6.441340782
Min length1

Characters and Unicode

Total characters4612
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique592 ?
Unique (%)82.7%

Sample

1st row16672.2
2nd row23243.7
3rd row86776.9
4th row20520.9
5th row19893.7
ValueCountFrequency (%)
48124 5
 
0.7%
0 4
 
0.6%
21602 3
 
0.4%
5135.8 3
 
0.4%
9653.9 3
 
0.4%
11683.9 2
 
0.3%
1840.3 2
 
0.3%
77814.1 2
 
0.3%
118732.9 2
 
0.3%
233 2
 
0.3%
Other values (640) 688
96.1%
2023-12-09T23:28:30.347222image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 625
13.6%
1 515
11.2%
2 451
9.8%
4 432
9.4%
3 425
9.2%
5 417
9.0%
9 380
8.2%
6 377
8.2%
7 372
8.1%
8 354
7.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3987
86.4%
Other Punctuation 625
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 515
12.9%
2 451
11.3%
4 432
10.8%
3 425
10.7%
5 417
10.5%
9 380
9.5%
6 377
9.5%
7 372
9.3%
8 354
8.9%
0 264
6.6%
Other Punctuation
ValueCountFrequency (%)
. 625
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4612
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 625
13.6%
1 515
11.2%
2 451
9.8%
4 432
9.4%
3 425
9.2%
5 417
9.0%
9 380
8.2%
6 377
8.2%
7 372
8.1%
8 354
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4612
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 625
13.6%
1 515
11.2%
2 451
9.8%
4 432
9.4%
3 425
9.2%
5 417
9.0%
9 380
8.2%
6 377
8.2%
7 372
8.1%
8 354
7.7%
Distinct787
Distinct (%)89.4%
Missing120
Missing (%)12.0%
Memory size60.3 KiB
2023-12-09T23:28:30.693764image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length11
Median length10
Mean length8.603409091
Min length1

Characters and Unicode

Total characters7571
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique705 ?
Unique (%)80.1%

Sample

1st row6551394.1
2nd row2564587.1
3rd row616343.7
4th row8033914.4
5th row1976691.9
ValueCountFrequency (%)
2249248.8 5
 
0.6%
3440512.5 4
 
0.5%
5183959.3 3
 
0.3%
36343152.6 3
 
0.3%
1989928 3
 
0.3%
85664.2 3
 
0.3%
3144282.1 3
 
0.3%
3636452.3 3
 
0.3%
1626453.3 2
 
0.2%
1546295.6 2
 
0.2%
Other values (777) 849
96.5%
2023-12-09T23:28:31.159674image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 886
11.7%
. 792
10.5%
2 744
9.8%
4 735
9.7%
3 694
9.2%
6 688
9.1%
5 678
9.0%
8 643
8.5%
7 616
8.1%
9 584
7.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6779
89.5%
Other Punctuation 792
 
10.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 886
13.1%
2 744
11.0%
4 735
10.8%
3 694
10.2%
6 688
10.1%
5 678
10.0%
8 643
9.5%
7 616
9.1%
9 584
8.6%
0 511
7.5%
Other Punctuation
ValueCountFrequency (%)
. 792
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7571
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 886
11.7%
. 792
10.5%
2 744
9.8%
4 735
9.7%
3 694
9.2%
6 688
9.1%
5 678
9.0%
8 643
8.5%
7 616
8.1%
9 584
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7571
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 886
11.7%
. 792
10.5%
2 744
9.8%
4 735
9.7%
3 694
9.2%
6 688
9.1%
5 678
9.0%
8 643
8.5%
7 616
8.1%
9 584
7.7%
Distinct787
Distinct (%)89.4%
Missing120
Missing (%)12.0%
Memory size59.7 KiB
2023-12-09T23:28:31.512982image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length10
Median length9
Mean length7.971590909
Min length1

Characters and Unicode

Total characters7015
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique705 ?
Unique (%)80.1%

Sample

1st row1920103.6
2nd row751637.4
3rd row180640
4th row2354605.3
5th row579335.2
ValueCountFrequency (%)
659217 5
 
0.6%
1008356.4 4
 
0.5%
25106.7 3
 
0.3%
583214.5 3
 
0.3%
1519331.4 3
 
0.3%
10651567.5 3
 
0.3%
1065783.1 3
 
0.3%
921536.2 3
 
0.3%
6597380.9 2
 
0.2%
25382.7 2
 
0.2%
Other values (777) 849
96.5%
2023-12-09T23:28:31.976399image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 801
11.4%
. 743
10.6%
2 705
10.0%
3 661
9.4%
9 641
9.1%
4 629
9.0%
6 610
8.7%
7 591
8.4%
5 585
8.3%
8 540
7.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6272
89.4%
Other Punctuation 743
 
10.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 801
12.8%
2 705
11.2%
3 661
10.5%
9 641
10.2%
4 629
10.0%
6 610
9.7%
7 591
9.4%
5 585
9.3%
8 540
8.6%
0 509
8.1%
Other Punctuation
ValueCountFrequency (%)
. 743
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7015
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 801
11.4%
. 743
10.6%
2 705
10.0%
3 661
9.4%
9 641
9.1%
4 629
9.0%
6 610
8.7%
7 591
8.4%
5 585
8.3%
8 540
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7015
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 801
11.4%
. 743
10.6%
2 705
10.0%
3 661
9.4%
9 641
9.1%
4 629
9.0%
6 610
8.7%
7 591
8.4%
5 585
8.3%
8 540
7.7%
Distinct748
Distinct (%)90.1%
Missing170
Missing (%)17.0%
Memory size58.1 KiB
2023-12-09T23:28:32.307255image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length10
Median length9
Mean length8.030120482
Min length1

Characters and Unicode

Total characters6665
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique676 ?
Unique (%)81.4%

Sample

1st row1920103.6
2nd row745273.8
3rd row184131.9
4th row2354605.3
5th row582516.1
ValueCountFrequency (%)
650622.9 5
 
0.6%
996961.6 4
 
0.5%
1052571.6 3
 
0.4%
573548.2 3
 
0.4%
10479019.5 3
 
0.4%
936810 3
 
0.4%
1516185.6 3
 
0.4%
297900 2
 
0.2%
38309.9 2
 
0.2%
508444.5 2
 
0.2%
Other values (738) 800
96.4%
2023-12-09T23:28:32.756831image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 749
11.2%
. 717
10.8%
2 669
10.0%
4 611
9.2%
3 610
9.2%
9 600
9.0%
5 595
8.9%
6 581
8.7%
8 558
8.4%
7 516
7.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5948
89.2%
Other Punctuation 717
 
10.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 749
12.6%
2 669
11.2%
4 611
10.3%
3 610
10.3%
9 600
10.1%
5 595
10.0%
6 581
9.8%
8 558
9.4%
7 516
8.7%
0 459
7.7%
Other Punctuation
ValueCountFrequency (%)
. 717
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6665
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 749
11.2%
. 717
10.8%
2 669
10.0%
4 611
9.2%
3 610
9.2%
9 600
9.0%
5 595
8.9%
6 581
8.7%
8 558
8.4%
7 516
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6665
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 749
11.2%
. 717
10.8%
2 669
10.0%
4 611
9.2%
3 610
9.2%
9 600
9.0%
5 595
8.9%
6 581
8.7%
8 558
8.4%
7 516
7.7%
Distinct787
Distinct (%)89.4%
Missing120
Missing (%)12.0%
Memory size60.2 KiB
2023-12-09T23:28:33.105063image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length11
Median length10
Mean length8.6
Min length1

Characters and Unicode

Total characters7568
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique705 ?
Unique (%)80.1%

Sample

1st row6551394.8
2nd row2564587.2
3rd row616343.7
4th row8033915.7
5th row1976692
ValueCountFrequency (%)
2249248.7 5
 
0.6%
3440514.1 4
 
0.5%
1989927.9 3
 
0.3%
36343156.8 3
 
0.3%
5183960.8 3
 
0.3%
85664.2 3
 
0.3%
3144282.2 3
 
0.3%
3636451.6 3
 
0.3%
634314.4 2
 
0.2%
5820059.9 2
 
0.2%
Other values (777) 849
96.5%
2023-12-09T23:28:33.575374image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 880
11.6%
. 789
10.4%
2 775
10.2%
4 726
9.6%
6 700
9.2%
3 696
9.2%
5 671
8.9%
8 635
8.4%
7 607
8.0%
9 579
7.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6779
89.6%
Other Punctuation 789
 
10.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 880
13.0%
2 775
11.4%
4 726
10.7%
6 700
10.3%
3 696
10.3%
5 671
9.9%
8 635
9.4%
7 607
9.0%
9 579
8.5%
0 510
7.5%
Other Punctuation
ValueCountFrequency (%)
. 789
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7568
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 880
11.6%
. 789
10.4%
2 775
10.2%
4 726
9.6%
6 700
9.2%
3 696
9.2%
5 671
8.9%
8 635
8.4%
7 607
8.0%
9 579
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7568
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 880
11.6%
. 789
10.4%
2 775
10.2%
4 726
9.6%
6 700
9.2%
3 696
9.2%
5 671
8.9%
8 635
8.4%
7 607
8.0%
9 579
7.7%
Distinct11
Distinct (%)73.3%
Missing985
Missing (%)98.5%
Memory size31.9 KiB
2023-12-09T23:28:33.782561image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.533333333
Min length5

Characters and Unicode

Total characters113
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)46.7%

Sample

1st row150869.6
2nd row193088.2
3rd row150869.6
4th row193088.2
5th row276.4
ValueCountFrequency (%)
150869.6 2
13.3%
311325.7 2
13.3%
614837.6 2
13.3%
193088.2 2
13.3%
132931.5 1
6.7%
173977.9 1
6.7%
276.4 1
6.7%
193187.4 1
6.7%
154973 1
6.7%
175035.6 1
6.7%
2023-12-09T23:28:34.099565image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 19
16.8%
3 16
14.2%
. 13
11.5%
6 11
9.7%
7 11
9.7%
5 9
8.0%
8 9
8.0%
9 9
8.0%
2 6
 
5.3%
0 5
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 100
88.5%
Other Punctuation 13
 
11.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 19
19.0%
3 16
16.0%
6 11
11.0%
7 11
11.0%
5 9
9.0%
8 9
9.0%
9 9
9.0%
2 6
 
6.0%
0 5
 
5.0%
4 5
 
5.0%
Other Punctuation
ValueCountFrequency (%)
. 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 113
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 19
16.8%
3 16
14.2%
. 13
11.5%
6 11
9.7%
7 11
9.7%
5 9
8.0%
8 9
8.0%
9 9
8.0%
2 6
 
5.3%
0 5
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 113
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 19
16.8%
3 16
14.2%
. 13
11.5%
6 11
9.7%
7 11
9.7%
5 9
8.0%
8 9
8.0%
9 9
8.0%
2 6
 
5.3%
0 5
 
4.4%
Distinct11
Distinct (%)73.3%
Missing985
Missing (%)98.5%
Memory size31.8 KiB
2023-12-09T23:28:34.294717image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length8
Median length7
Mean length6
Min length2

Characters and Unicode

Total characters90
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)46.7%

Sample

1st row44217.4
2nd row56590.9
3rd row44217.4
4th row56590.9
5th row81
ValueCountFrequency (%)
91244.3 2
13.3%
180198.6 2
13.3%
44217.4 2
13.3%
56590.9 2
13.3%
45420 1
6.7%
51300 1
6.7%
81 1
6.7%
38960 1
6.7%
50990 1
6.7%
56620 1
6.7%
2023-12-09T23:28:34.608386image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 12
13.3%
0 12
13.3%
9 11
12.2%
1 10
11.1%
5 9
10.0%
. 8
8.9%
8 8
8.9%
6 7
7.8%
2 6
6.7%
3 5
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 82
91.1%
Other Punctuation 8
 
8.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 12
14.6%
0 12
14.6%
9 11
13.4%
1 10
12.2%
5 9
11.0%
8 8
9.8%
6 7
8.5%
2 6
7.3%
3 5
6.1%
7 2
 
2.4%
Other Punctuation
ValueCountFrequency (%)
. 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 90
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 12
13.3%
0 12
13.3%
9 11
12.2%
1 10
11.1%
5 9
10.0%
. 8
8.9%
8 8
8.9%
6 7
7.8%
2 6
6.7%
3 5
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 12
13.3%
0 12
13.3%
9 11
12.2%
1 10
11.1%
5 9
10.0%
. 8
8.9%
8 8
8.9%
6 7
7.8%
2 6
6.7%
3 5
5.6%

electricity_use_generated_2
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)6.7%
Missing985
Missing (%)98.5%
Memory size31.8 KiB
2023-12-09T23:28:34.714306image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters15
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 15
100.0%
2023-12-09T23:28:34.924487image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 15
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 15
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 15
100.0%
Distinct28
Distinct (%)87.5%
Missing968
Missing (%)96.8%
Memory size32.3 KiB
2023-12-09T23:28:35.140096image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length6
Mean length4
Min length2

Characters and Unicode

Total characters128
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)75.0%

Sample

1st row408
2nd row985.4
3rd row102.4
4th row102.4
5th row96
ValueCountFrequency (%)
102.4 2
 
6.2%
42.4 2
 
6.2%
72 2
 
6.2%
456 2
 
6.2%
5460.9 1
 
3.1%
208 1
 
3.1%
4041 1
 
3.1%
96 1
 
3.1%
5616 1
 
3.1%
320 1
 
3.1%
Other values (18) 18
56.2%
2023-12-09T23:28:35.480646image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 21
16.4%
0 17
13.3%
8 14
10.9%
1 13
10.2%
2 13
10.2%
. 12
9.4%
6 9
7.0%
9 9
7.0%
5 7
 
5.5%
7 7
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 116
90.6%
Other Punctuation 12
 
9.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 21
18.1%
0 17
14.7%
8 14
12.1%
1 13
11.2%
2 13
11.2%
6 9
7.8%
9 9
7.8%
5 7
 
6.0%
7 7
 
6.0%
3 6
 
5.2%
Other Punctuation
ValueCountFrequency (%)
. 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 128
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 21
16.4%
0 17
13.3%
8 14
10.9%
1 13
10.2%
2 13
10.2%
. 12
9.4%
6 9
7.0%
9 9
7.0%
5 7
 
5.5%
7 7
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 128
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 21
16.4%
0 17
13.3%
8 14
10.9%
1 13
10.2%
2 13
10.2%
. 12
9.4%
6 9
7.0%
9 9
7.0%
5 7
 
5.5%
7 7
 
5.5%
Distinct8
Distinct (%)25.0%
Missing968
Missing (%)96.8%
Memory size32.9 KiB
2023-12-09T23:28:35.685097image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length23
Median length23
Mean length23
Min length23

Characters and Unicode

Total characters736
Distinct characters12
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)3.1%

Sample

1st row2017-08-01T00:00:00.000
2nd row2017-09-01T00:00:00.000
3rd row2017-08-01T00:00:00.000
4th row2017-08-01T00:00:00.000
5th row2017-07-01T00:00:00.000
ValueCountFrequency (%)
2017-08-01t00:00:00.000 10
31.2%
2017-01-01t00:00:00.000 6
18.8%
2017-07-01t00:00:00.000 5
15.6%
2017-09-01t00:00:00.000 4
 
12.5%
2017-06-01t00:00:00.000 2
 
6.2%
2017-11-01t00:00:00.000 2
 
6.2%
2017-10-01t00:00:00.000 2
 
6.2%
2017-05-01t00:00:00.000 1
 
3.1%
2023-12-09T23:28:35.996169image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 382
51.9%
1 76
 
10.3%
- 64
 
8.7%
: 64
 
8.7%
7 37
 
5.0%
2 32
 
4.3%
T 32
 
4.3%
. 32
 
4.3%
8 10
 
1.4%
9 4
 
0.5%
Other values (2) 3
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 544
73.9%
Other Punctuation 96
 
13.0%
Dash Punctuation 64
 
8.7%
Uppercase Letter 32
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 382
70.2%
1 76
 
14.0%
7 37
 
6.8%
2 32
 
5.9%
8 10
 
1.8%
9 4
 
0.7%
6 2
 
0.4%
5 1
 
0.2%
Other Punctuation
ValueCountFrequency (%)
: 64
66.7%
. 32
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 64
100.0%
Uppercase Letter
ValueCountFrequency (%)
T 32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 704
95.7%
Latin 32
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 382
54.3%
1 76
 
10.8%
- 64
 
9.1%
: 64
 
9.1%
7 37
 
5.3%
2 32
 
4.5%
. 32
 
4.5%
8 10
 
1.4%
9 4
 
0.6%
6 2
 
0.3%
Latin
ValueCountFrequency (%)
T 32
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 736
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 382
51.9%
1 76
 
10.3%
- 64
 
8.7%
: 64
 
8.7%
7 37
 
5.0%
2 32
 
4.3%
T 32
 
4.3%
. 32
 
4.3%
8 10
 
1.4%
9 4
 
0.5%
Other values (2) 3
 
0.4%
Distinct28
Distinct (%)87.5%
Missing968
Missing (%)96.8%
Memory size33.1 KiB
2023-12-09T23:28:36.275224image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length50
Median length33.5
Mean length29.8125
Min length18

Characters and Unicode

Total characters954
Distinct characters35
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)75.0%

Sample

1st rowElectric (4054489)
2nd rowElectric Grid Meter (26121539)
3rd rowElectric Grid Meter #2 (28045557)
4th rowElectric Grid Meter #2 (28045557)
5th rowMETER#6725796 (4876145)
ValueCountFrequency (%)
electric 10
 
10.8%
grid 6
 
6.5%
meter 6
 
6.5%
electricity 5
 
5.4%
ac 4
 
4.3%
40723396 2
 
2.2%
494202304800001 2
 
2.2%
29-9101-0153-0000-3 2
 
2.2%
2 2
 
2.2%
4151337 2
 
2.2%
Other values (49) 52
55.9%
2023-12-09T23:28:36.694319image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 124
 
13.0%
4 63
 
6.6%
61
 
6.4%
1 57
 
6.0%
2 56
 
5.9%
3 53
 
5.6%
5 52
 
5.5%
8 49
 
5.1%
9 42
 
4.4%
6 38
 
4.0%
Other values (25) 359
37.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 559
58.6%
Lowercase Letter 188
 
19.7%
Space Separator 61
 
6.4%
Uppercase Letter 48
 
5.0%
Open Punctuation 32
 
3.4%
Close Punctuation 32
 
3.4%
Dash Punctuation 28
 
2.9%
Other Punctuation 6
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
c 34
18.1%
e 28
14.9%
i 28
14.9%
r 28
14.9%
t 28
14.9%
l 18
9.6%
d 8
 
4.3%
y 5
 
2.7%
o 4
 
2.1%
n 4
 
2.1%
Other values (3) 3
 
1.6%
Decimal Number
ValueCountFrequency (%)
0 124
22.2%
4 63
11.3%
1 57
10.2%
2 56
10.0%
3 53
9.5%
5 52
9.3%
8 49
 
8.8%
9 42
 
7.5%
6 38
 
6.8%
7 25
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
E 20
41.7%
M 7
 
14.6%
C 6
 
12.5%
G 6
 
12.5%
A 5
 
10.4%
R 3
 
6.2%
T 1
 
2.1%
Space Separator
ValueCountFrequency (%)
61
100.0%
Open Punctuation
ValueCountFrequency (%)
( 32
100.0%
Close Punctuation
ValueCountFrequency (%)
) 32
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 28
100.0%
Other Punctuation
ValueCountFrequency (%)
# 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 718
75.3%
Latin 236
 
24.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
c 34
14.4%
e 28
11.9%
i 28
11.9%
r 28
11.9%
t 28
11.9%
E 20
8.5%
l 18
7.6%
d 8
 
3.4%
M 7
 
3.0%
C 6
 
2.5%
Other values (10) 31
13.1%
Common
ValueCountFrequency (%)
0 124
17.3%
4 63
8.8%
61
8.5%
1 57
7.9%
2 56
7.8%
3 53
7.4%
5 52
7.2%
8 49
 
6.8%
9 42
 
5.8%
6 38
 
5.3%
Other values (5) 123
17.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 954
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 124
 
13.0%
4 63
 
6.6%
61
 
6.4%
1 57
 
6.0%
2 56
 
5.9%
3 53
 
5.6%
5 52
 
5.5%
8 49
 
5.1%
9 42
 
4.4%
6 38
 
4.0%
Other values (25) 359
37.6%
Distinct11
Distinct (%)73.3%
Missing985
Missing (%)98.5%
Memory size31.8 KiB
2023-12-09T23:28:36.898514image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length8
Median length7
Mean length6
Min length2

Characters and Unicode

Total characters90
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)46.7%

Sample

1st row44217.4
2nd row53552.9
3rd row44217.4
4th row53552.9
5th row81
ValueCountFrequency (%)
91244.3 2
13.3%
180198.6 2
13.3%
44217.4 2
13.3%
53552.9 2
13.3%
45420 1
6.7%
51300 1
6.7%
81 1
6.7%
38960 1
6.7%
50990 1
6.7%
56620 1
6.7%
2023-12-09T23:28:37.215116image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 12
13.3%
5 11
12.2%
1 10
11.1%
0 10
11.1%
9 9
10.0%
2 8
8.9%
. 8
8.9%
8 8
8.9%
3 7
7.8%
6 5
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 82
91.1%
Other Punctuation 8
 
8.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 12
14.6%
5 11
13.4%
1 10
12.2%
0 10
12.2%
9 9
11.0%
2 8
9.8%
8 8
9.8%
3 7
8.5%
6 5
6.1%
7 2
 
2.4%
Other Punctuation
ValueCountFrequency (%)
. 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 90
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 12
13.3%
5 11
12.2%
1 10
11.1%
0 10
11.1%
9 9
10.0%
2 8
8.9%
. 8
8.9%
8 8
8.9%
3 7
7.8%
6 5
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 12
13.3%
5 11
12.2%
1 10
11.1%
0 10
11.1%
9 9
10.0%
2 8
8.9%
. 8
8.9%
8 8
8.9%
3 7
7.8%
6 5
5.6%
Distinct2
Distinct (%)0.2%
Missing120
Missing (%)12.0%
Memory size53.7 KiB
2023-12-09T23:28:37.343559image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length1
Mean length1.006818182
Min length1

Characters and Unicode

Total characters886
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row1805758
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 879
99.9%
1805758 1
 
0.1%
2023-12-09T23:28:37.589913image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 880
99.3%
8 2
 
0.2%
5 2
 
0.2%
1 1
 
0.1%
7 1
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 886
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 880
99.3%
8 2
 
0.2%
5 2
 
0.2%
1 1
 
0.1%
7 1
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 886
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 880
99.3%
8 2
 
0.2%
5 2
 
0.2%
1 1
 
0.1%
7 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 886
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 880
99.3%
8 2
 
0.2%
5 2
 
0.2%
1 1
 
0.1%
7 1
 
0.1%
Distinct11
Distinct (%)73.3%
Missing985
Missing (%)98.5%
Memory size31.8 KiB
2023-12-09T23:28:37.779372image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.8
Min length1

Characters and Unicode

Total characters57
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)46.7%

Sample

1st row26.4
2nd row31.9
3rd row26.4
4th row31.9
5th row0
ValueCountFrequency (%)
107.4 2
13.3%
26.4 2
13.3%
31.9 2
13.3%
54.4 2
13.3%
27.1 1
6.7%
33.8 1
6.7%
30.6 1
6.7%
23.2 1
6.7%
0 1
6.7%
23 1
6.7%
2023-12-09T23:28:38.115445image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 13
22.8%
4 9
15.8%
3 8
14.0%
2 6
10.5%
1 5
 
8.8%
0 5
 
8.8%
7 3
 
5.3%
6 3
 
5.3%
9 2
 
3.5%
5 2
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 44
77.2%
Other Punctuation 13
 
22.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 9
20.5%
3 8
18.2%
2 6
13.6%
1 5
11.4%
0 5
11.4%
7 3
 
6.8%
6 3
 
6.8%
9 2
 
4.5%
5 2
 
4.5%
8 1
 
2.3%
Other Punctuation
ValueCountFrequency (%)
. 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 57
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 13
22.8%
4 9
15.8%
3 8
14.0%
2 6
10.5%
1 5
 
8.8%
0 5
 
8.8%
7 3
 
5.3%
6 3
 
5.3%
9 2
 
3.5%
5 2
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 57
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 13
22.8%
4 9
15.8%
3 8
14.0%
2 6
10.5%
1 5
 
8.8%
0 5
 
8.8%
7 3
 
5.3%
6 3
 
5.3%
9 2
 
3.5%
5 2
 
3.5%
Distinct2
Distinct (%)0.2%
Missing114
Missing (%)11.4%
Memory size53.9 KiB
2023-12-09T23:28:38.235577image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.004514673
Min length1

Characters and Unicode

Total characters890
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row597.4
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 885
99.9%
597.4 1
 
0.1%
2023-12-09T23:28:38.471565image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 885
99.4%
5 1
 
0.1%
9 1
 
0.1%
7 1
 
0.1%
. 1
 
0.1%
4 1
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 889
99.9%
Other Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 885
99.6%
5 1
 
0.1%
9 1
 
0.1%
7 1
 
0.1%
4 1
 
0.1%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 890
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 885
99.4%
5 1
 
0.1%
9 1
 
0.1%
7 1
 
0.1%
. 1
 
0.1%
4 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 890
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 885
99.4%
5 1
 
0.1%
9 1
 
0.1%
7 1
 
0.1%
. 1
 
0.1%
4 1
 
0.1%
Distinct779
Distinct (%)82.6%
Missing57
Missing (%)5.7%
Memory size58.8 KiB
2023-12-09T23:28:38.892382image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length8
Median length5
Mean length4.801696713
Min length1

Characters and Unicode

Total characters4528
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique673 ?
Unique (%)71.4%

Sample

1st row732.4
2nd row284.8
3rd row164.5
4th row1150.2
5th row273.4
ValueCountFrequency (%)
0 45
 
4.8%
434.3 6
 
0.6%
305 4
 
0.4%
322.4 3
 
0.3%
770.1 3
 
0.3%
194.8 3
 
0.3%
227.7 3
 
0.3%
278.8 3
 
0.3%
309.6 3
 
0.3%
52.7 3
 
0.3%
Other values (769) 867
91.9%
2023-12-09T23:28:39.467513image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 812
17.9%
2 495
10.9%
1 472
10.4%
3 443
9.8%
4 406
9.0%
6 355
7.8%
5 336
7.4%
8 336
7.4%
7 336
7.4%
0 270
 
6.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3716
82.1%
Other Punctuation 812
 
17.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 495
13.3%
1 472
12.7%
3 443
11.9%
4 406
10.9%
6 355
9.6%
5 336
9.0%
8 336
9.0%
7 336
9.0%
0 270
7.3%
9 267
7.2%
Other Punctuation
ValueCountFrequency (%)
. 812
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4528
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 812
17.9%
2 495
10.9%
1 472
10.4%
3 443
9.8%
4 406
9.0%
6 355
7.8%
5 336
7.4%
8 336
7.4%
7 336
7.4%
0 270
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4528
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 812
17.9%
2 495
10.9%
1 472
10.4%
3 443
9.8%
4 406
9.0%
6 355
7.8%
5 336
7.4%
8 336
7.4%
7 336
7.4%
0 270
 
6.0%
Distinct666
Distinct (%)70.2%
Missing51
Missing (%)5.1%
Memory size58.3 KiB
2023-12-09T23:28:39.933703image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length5
Mean length4.044257113
Min length1

Characters and Unicode

Total characters3838
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique558 ?
Unique (%)58.8%

Sample

1st row76.3
2nd row57.4
3rd row109.9
4th row438
5th row98.2
ValueCountFrequency (%)
0 158
 
16.6%
234.9 5
 
0.5%
132.6 4
 
0.4%
109.1 3
 
0.3%
1.9 3
 
0.3%
51.3 3
 
0.3%
114.7 3
 
0.3%
1.1 3
 
0.3%
216.1 3
 
0.3%
10.8 3
 
0.3%
Other values (656) 761
80.2%
2023-12-09T23:28:41.056258image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 726
18.9%
1 459
12.0%
2 408
10.6%
3 379
9.9%
0 312
8.1%
4 305
7.9%
6 270
 
7.0%
5 269
 
7.0%
7 239
 
6.2%
9 237
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3112
81.1%
Other Punctuation 726
 
18.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 459
14.7%
2 408
13.1%
3 379
12.2%
0 312
10.0%
4 305
9.8%
6 270
8.7%
5 269
8.6%
7 239
7.7%
9 237
7.6%
8 234
7.5%
Other Punctuation
ValueCountFrequency (%)
. 726
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3838
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 726
18.9%
1 459
12.0%
2 408
10.6%
3 379
9.9%
0 312
8.1%
4 305
7.9%
6 270
 
7.0%
5 269
 
7.0%
7 239
 
6.2%
9 237
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3838
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 726
18.9%
1 459
12.0%
2 408
10.6%
3 379
9.9%
0 312
8.1%
4 305
7.9%
6 270
 
7.0%
5 269
 
7.0%
7 239
 
6.2%
9 237
 
6.2%
Distinct727
Distinct (%)76.8%
Missing53
Missing (%)5.3%
Memory size58.5 KiB
2023-12-09T23:28:41.533854image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length8
Median length7
Mean length4.316789863
Min length1

Characters and Unicode

Total characters4088
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique603 ?
Unique (%)63.7%

Sample

1st row656.1
2nd row227.4
3rd row54.6
4th row712.3
5th row175.3
ValueCountFrequency (%)
0 72
 
7.6%
199.4 5
 
0.5%
14.5 4
 
0.4%
176.4 4
 
0.4%
305 4
 
0.4%
7.6 4
 
0.4%
278.8 3
 
0.3%
770.1 3
 
0.3%
59 3
 
0.3%
60.4 3
 
0.3%
Other values (717) 842
88.9%
2023-12-09T23:28:42.147859image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 779
19.1%
1 498
12.2%
2 397
9.7%
4 353
8.6%
3 324
7.9%
6 321
7.9%
5 317
7.8%
7 295
 
7.2%
8 276
 
6.8%
9 270
 
6.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3309
80.9%
Other Punctuation 779
 
19.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 498
15.0%
2 397
12.0%
4 353
10.7%
3 324
9.8%
6 321
9.7%
5 317
9.6%
7 295
8.9%
8 276
8.3%
9 270
8.2%
0 258
7.8%
Other Punctuation
ValueCountFrequency (%)
. 779
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4088
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 779
19.1%
1 498
12.2%
2 397
9.7%
4 353
8.6%
3 324
7.9%
6 321
7.9%
5 317
7.8%
7 295
 
7.2%
8 276
 
6.8%
9 270
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4088
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 779
19.1%
1 498
12.2%
2 397
9.7%
4 353
8.6%
3 324
7.9%
6 321
7.9%
5 317
7.8%
7 295
 
7.2%
8 276
 
6.8%
9 270
 
6.6%
Distinct864
Distinct (%)88.4%
Missing23
Missing (%)2.3%
Memory size60.1 KiB
2023-12-09T23:28:42.585778image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.060388946
Min length1

Characters and Unicode

Total characters4944
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique771 ?
Unique (%)78.9%

Sample

1st row1340
2nd row201.8
3rd row548.6
4th row1649.2
5th row221.8
ValueCountFrequency (%)
418.8 4
 
0.4%
718.9 4
 
0.4%
435 3
 
0.3%
297.1 3
 
0.3%
600.4 3
 
0.3%
443.7 3
 
0.3%
189.7 3
 
0.3%
768.8 3
 
0.3%
507.9 3
 
0.3%
10940.2 3
 
0.3%
Other values (854) 945
96.7%
2023-12-09T23:28:43.149392image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 873
17.7%
1 553
11.2%
2 524
10.6%
3 508
10.3%
4 437
8.8%
5 379
7.7%
6 367
7.4%
7 361
7.3%
8 359
7.3%
9 344
 
7.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4071
82.3%
Other Punctuation 873
 
17.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 553
13.6%
2 524
12.9%
3 508
12.5%
4 437
10.7%
5 379
9.3%
6 367
9.0%
7 361
8.9%
8 359
8.8%
9 344
8.5%
0 239
5.9%
Other Punctuation
ValueCountFrequency (%)
. 873
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4944
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 873
17.7%
1 553
11.2%
2 524
10.6%
3 508
10.3%
4 437
8.8%
5 379
7.7%
6 367
7.4%
7 361
7.3%
8 359
7.3%
9 344
 
7.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4944
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 873
17.7%
1 553
11.2%
2 524
10.6%
3 508
10.3%
4 437
8.8%
5 379
7.7%
6 367
7.4%
7 361
7.3%
8 359
7.3%
9 344
 
7.0%

estimated_data_flag
Text

MISSING 

Distinct2
Distinct (%)0.2%
Missing59
Missing (%)5.9%
Memory size56.2 KiB
2023-12-09T23:28:43.276241image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.055260361
Min length2

Characters and Unicode

Total characters1934
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 889
94.5%
yes 52
 
5.5%
2023-12-09T23:28:43.496678image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 889
46.0%
o 889
46.0%
Y 52
 
2.7%
e 52
 
2.7%
s 52
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 993
51.3%
Uppercase Letter 941
48.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 889
89.5%
e 52
 
5.2%
s 52
 
5.2%
Uppercase Letter
ValueCountFrequency (%)
N 889
94.5%
Y 52
 
5.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 1934
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 889
46.0%
o 889
46.0%
Y 52
 
2.7%
e 52
 
2.7%
s 52
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1934
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 889
46.0%
o 889
46.0%
Y 52
 
2.7%
e 52
 
2.7%
s 52
 
2.7%
Distinct2
Distinct (%)0.2%
Missing175
Missing (%)17.5%
Memory size53.2 KiB
2023-12-09T23:28:43.604488image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.042424242
Min length2

Characters and Unicode

Total characters1685
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 790
95.8%
yes 35
 
4.2%
2023-12-09T23:28:43.821536image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 790
46.9%
o 790
46.9%
Y 35
 
2.1%
e 35
 
2.1%
s 35
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 860
51.0%
Uppercase Letter 825
49.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 790
91.9%
e 35
 
4.1%
s 35
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
N 790
95.8%
Y 35
 
4.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 1685
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 790
46.9%
o 790
46.9%
Y 35
 
2.1%
e 35
 
2.1%
s 35
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1685
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 790
46.9%
o 790
46.9%
Y 35
 
2.1%
e 35
 
2.1%
s 35
 
2.1%
Distinct2
Distinct (%)1.0%
Missing803
Missing (%)80.3%
Memory size36.6 KiB
2023-12-09T23:28:43.928954image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.025380711
Min length2

Characters and Unicode

Total characters399
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 192
97.5%
yes 5
 
2.5%
2023-12-09T23:28:44.151770image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 192
48.1%
o 192
48.1%
Y 5
 
1.3%
e 5
 
1.3%
s 5
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 202
50.6%
Uppercase Letter 197
49.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 192
95.0%
e 5
 
2.5%
s 5
 
2.5%
Uppercase Letter
ValueCountFrequency (%)
N 192
97.5%
Y 5
 
2.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 399
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 192
48.1%
o 192
48.1%
Y 5
 
1.3%
e 5
 
1.3%
s 5
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 399
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 192
48.1%
o 192
48.1%
Y 5
 
1.3%
e 5
 
1.3%
s 5
 
1.3%
Distinct2
Distinct (%)1.9%
Missing897
Missing (%)89.7%
Memory size34.1 KiB
2023-12-09T23:28:44.271515image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.019417476
Min length2

Characters and Unicode

Total characters208
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowYes
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 101
98.1%
yes 2
 
1.9%
2023-12-09T23:28:44.491068image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 101
48.6%
o 101
48.6%
Y 2
 
1.0%
e 2
 
1.0%
s 2
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 105
50.5%
Uppercase Letter 103
49.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 101
96.2%
e 2
 
1.9%
s 2
 
1.9%
Uppercase Letter
ValueCountFrequency (%)
N 101
98.1%
Y 2
 
1.9%

Most occurring scripts

ValueCountFrequency (%)
Latin 208
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 101
48.6%
o 101
48.6%
Y 2
 
1.0%
e 2
 
1.0%
s 2
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 208
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 101
48.6%
o 101
48.6%
Y 2
 
1.0%
e 2
 
1.0%
s 2
 
1.0%
Distinct2
Distinct (%)3.4%
Missing942
Missing (%)94.2%
Memory size32.9 KiB
2023-12-09T23:28:44.597907image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.017241379
Min length2

Characters and Unicode

Total characters117
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)1.7%

Sample

1st rowNo
2nd rowNo
3rd rowYes
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 57
98.3%
yes 1
 
1.7%
2023-12-09T23:28:44.815893image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 57
48.7%
o 57
48.7%
Y 1
 
0.9%
e 1
 
0.9%
s 1
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 59
50.4%
Uppercase Letter 58
49.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 57
96.6%
e 1
 
1.7%
s 1
 
1.7%
Uppercase Letter
ValueCountFrequency (%)
N 57
98.3%
Y 1
 
1.7%

Most occurring scripts

ValueCountFrequency (%)
Latin 117
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 57
48.7%
o 57
48.7%
Y 1
 
0.9%
e 1
 
0.9%
s 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 117
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 57
48.7%
o 57
48.7%
Y 1
 
0.9%
e 1
 
0.9%
s 1
 
0.9%

estimated_data_flag_district
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)0.7%
Missing866
Missing (%)86.6%
Memory size34.9 KiB
2023-12-09T23:28:44.915183image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters268
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 134
100.0%
2023-12-09T23:28:45.128702image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 134
50.0%
o 134
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 134
50.0%
Lowercase Letter 134
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 134
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 134
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 268
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 134
50.0%
o 134
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 268
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 134
50.0%
o 134
50.0%
Distinct7
Distinct (%)0.7%
Missing1
Missing (%)0.1%
Memory size59.7 KiB
2023-12-09T23:28:45.269984image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.009009009
Min length3

Characters and Unicode

Total characters4005
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)0.4%

Sample

1st row88.7
2nd row88.7
3rd row88.7
4th row88.7
5th row88.7
ValueCountFrequency (%)
88.7 986
98.7%
160.1 5
 
0.5%
237.4 4
 
0.4%
178.9 1
 
0.1%
153 1
 
0.1%
84.7 1
 
0.1%
48.9 1
 
0.1%
2023-12-09T23:28:45.545002image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 1975
49.3%
. 998
24.9%
7 992
24.8%
1 12
 
0.3%
4 6
 
0.1%
6 5
 
0.1%
0 5
 
0.1%
3 5
 
0.1%
2 4
 
0.1%
9 2
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3007
75.1%
Other Punctuation 998
 
24.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 1975
65.7%
7 992
33.0%
1 12
 
0.4%
4 6
 
0.2%
6 5
 
0.2%
0 5
 
0.2%
3 5
 
0.2%
2 4
 
0.1%
9 2
 
0.1%
5 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 998
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4005
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 1975
49.3%
. 998
24.9%
7 992
24.8%
1 12
 
0.3%
4 6
 
0.1%
6 5
 
0.1%
0 5
 
0.1%
3 5
 
0.1%
2 4
 
0.1%
9 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4005
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 1975
49.3%
. 998
24.9%
7 992
24.8%
1 12
 
0.3%
4 6
 
0.1%
6 5
 
0.1%
0 5
 
0.1%
3 5
 
0.1%
2 4
 
0.1%
9 2
 
< 0.1%
Distinct778
Distinct (%)81.6%
Missing46
Missing (%)4.6%
Memory size59.1 KiB
2023-12-09T23:28:46.015510image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length8
Median length5
Mean length4.757861635
Min length1

Characters and Unicode

Total characters4539
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique671 ?
Unique (%)70.3%

Sample

1st row134.9
2nd row284.8
3rd row164.5
4th row1150.2
5th row273.4
ValueCountFrequency (%)
0 56
 
5.9%
434.3 6
 
0.6%
305 4
 
0.4%
322.4 3
 
0.3%
770.1 3
 
0.3%
194.8 3
 
0.3%
227.7 3
 
0.3%
278.8 3
 
0.3%
309.6 3
 
0.3%
52.7 3
 
0.3%
Other values (768) 867
90.9%
2023-12-09T23:28:46.648037image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 812
17.9%
2 494
10.9%
1 473
10.4%
3 443
9.8%
4 406
8.9%
6 355
7.8%
5 336
7.4%
8 336
7.4%
7 335
7.4%
0 281
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3727
82.1%
Other Punctuation 812
 
17.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 494
13.3%
1 473
12.7%
3 443
11.9%
4 406
10.9%
6 355
9.5%
5 336
9.0%
8 336
9.0%
7 335
9.0%
0 281
7.5%
9 268
7.2%
Other Punctuation
ValueCountFrequency (%)
. 812
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4539
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 812
17.9%
2 494
10.9%
1 473
10.4%
3 443
9.8%
4 406
8.9%
6 355
7.8%
5 336
7.4%
8 336
7.4%
7 335
7.4%
0 281
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4539
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 812
17.9%
2 494
10.9%
1 473
10.4%
3 443
9.8%
4 406
8.9%
6 355
7.8%
5 336
7.4%
8 336
7.4%
7 335
7.4%
0 281
 
6.2%
Distinct14
Distinct (%)1.6%
Missing121
Missing (%)12.1%
Memory size54.0 KiB
2023-12-09T23:28:46.868677image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length11
Median length1
Mean length1.33105802
Min length1

Characters and Unicode

Total characters1170
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)0.9%

Sample

1st row94.0448
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 804
91.5%
0.00 59
 
6.7%
15.15304 2
 
0.2%
49.08065 2
 
0.2%
43.02897 2
 
0.2%
4.972456 2
 
0.2%
7.652524 1
 
0.1%
8.948941 1
 
0.1%
14.91325 1
 
0.1%
15.39521 1
 
0.1%
Other values (4) 4
 
0.5%
2023-12-09T23:28:47.169421image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 993
84.9%
. 75
 
6.4%
4 19
 
1.6%
5 14
 
1.2%
2 14
 
1.2%
1 12
 
1.0%
9 12
 
1.0%
8 9
 
0.8%
7 8
 
0.7%
3 7
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1095
93.6%
Other Punctuation 75
 
6.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 993
90.7%
4 19
 
1.7%
5 14
 
1.3%
2 14
 
1.3%
1 12
 
1.1%
9 12
 
1.1%
8 9
 
0.8%
7 8
 
0.7%
3 7
 
0.6%
6 7
 
0.6%
Other Punctuation
ValueCountFrequency (%)
. 75
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1170
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 993
84.9%
. 75
 
6.4%
4 19
 
1.6%
5 14
 
1.2%
2 14
 
1.2%
1 12
 
1.0%
9 12
 
1.0%
8 9
 
0.8%
7 8
 
0.7%
3 7
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1170
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 993
84.9%
. 75
 
6.4%
4 19
 
1.6%
5 14
 
1.2%
2 14
 
1.2%
1 12
 
1.0%
9 12
 
1.0%
8 9
 
0.8%
7 8
 
0.7%
3 7
 
0.6%
Distinct2
Distinct (%)13.3%
Missing985
Missing (%)98.5%
Memory size31.8 KiB
2023-12-09T23:28:47.313513image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.666666667
Min length3

Characters and Unicode

Total characters55
Distinct characters8
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row100
2nd row94.63165
3rd row100
4th row94.63165
5th row100
ValueCountFrequency (%)
100 13
86.7%
94.63165 2
 
13.3%
2023-12-09T23:28:47.593009image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 26
47.3%
1 15
27.3%
6 4
 
7.3%
9 2
 
3.6%
4 2
 
3.6%
. 2
 
3.6%
3 2
 
3.6%
5 2
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 53
96.4%
Other Punctuation 2
 
3.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 26
49.1%
1 15
28.3%
6 4
 
7.5%
9 2
 
3.8%
4 2
 
3.8%
3 2
 
3.8%
5 2
 
3.8%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 55
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 26
47.3%
1 15
27.3%
6 4
 
7.3%
9 2
 
3.6%
4 2
 
3.6%
. 2
 
3.6%
3 2
 
3.6%
5 2
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 55
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 26
47.3%
1 15
27.3%
6 4
 
7.3%
9 2
 
3.6%
4 2
 
3.6%
. 2
 
3.6%
3 2
 
3.6%
5 2
 
3.6%
Distinct11
Distinct (%)73.3%
Missing985
Missing (%)98.5%
Memory size31.9 KiB
2023-12-09T23:28:47.807786image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length11
Median length8
Mean length8.2
Min length8

Characters and Unicode

Total characters123
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)46.7%

Sample

1st row15.15304
2nd row5.254538
3rd row15.15304
4th row5.254538
5th row0.004223576
ValueCountFrequency (%)
15.15304 2
13.3%
5.254538 2
13.3%
43.02897 2
13.3%
49.08065 2
13.3%
7.652524 1
6.7%
8.948941 1
6.7%
15.39521 1
6.7%
0.004223576 1
6.7%
18.89722 1
6.7%
12.62471 1
6.7%
2023-12-09T23:28:48.133212image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 18
14.6%
. 15
12.2%
4 14
11.4%
2 14
11.4%
1 12
9.8%
0 11
8.9%
8 10
8.1%
3 9
7.3%
9 9
7.3%
7 6
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 108
87.8%
Other Punctuation 15
 
12.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 18
16.7%
4 14
13.0%
2 14
13.0%
1 12
11.1%
0 11
10.2%
8 10
9.3%
3 9
8.3%
9 9
8.3%
7 6
 
5.6%
6 5
 
4.6%
Other Punctuation
ValueCountFrequency (%)
. 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 123
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 18
14.6%
. 15
12.2%
4 14
11.4%
2 14
11.4%
1 12
9.8%
0 11
8.9%
8 10
8.1%
3 9
7.3%
9 9
7.3%
7 6
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 123
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 18
14.6%
. 15
12.2%
4 14
11.4%
2 14
11.4%
1 12
9.8%
0 11
8.9%
8 10
8.1%
3 9
7.3%
9 9
7.3%
7 6
 
4.9%

costar_property_id
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1000
Missing (%)100.0%
Memory size7.9 KiB

leed_us_project_id
Text

MISSING 

Distinct14
Distinct (%)87.5%
Missing984
Missing (%)98.4%
Memory size31.9 KiB
2023-12-09T23:28:48.345662image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.75
Min length8

Characters and Unicode

Total characters156
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)75.0%

Sample

1st row1000077349
2nd row1000016631
3rd row1000005367
4th row10422392
5th row1000018067
ValueCountFrequency (%)
10422392 2
12.5%
1000005367 2
12.5%
1000093438 1
 
6.2%
1000024211 1
 
6.2%
1000016631 1
 
6.2%
1000077668 1
 
6.2%
1000093327 1
 
6.2%
1000077349 1
 
6.2%
1000099043 1
 
6.2%
1000078681 1
 
6.2%
Other values (4) 4
25.0%
2023-12-09T23:28:48.705966image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 66
42.3%
1 23
 
14.7%
3 12
 
7.7%
7 11
 
7.1%
2 10
 
6.4%
9 9
 
5.8%
4 8
 
5.1%
6 8
 
5.1%
8 6
 
3.8%
5 3
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 156
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 66
42.3%
1 23
 
14.7%
3 12
 
7.7%
7 11
 
7.1%
2 10
 
6.4%
9 9
 
5.8%
4 8
 
5.1%
6 8
 
5.1%
8 6
 
3.8%
5 3
 
1.9%

Most occurring scripts

ValueCountFrequency (%)
Common 156
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 66
42.3%
1 23
 
14.7%
3 12
 
7.7%
7 11
 
7.1%
2 10
 
6.4%
9 9
 
5.8%
4 8
 
5.1%
6 8
 
5.1%
8 6
 
3.8%
5 3
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 156
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 66
42.3%
1 23
 
14.7%
3 12
 
7.7%
7 11
 
7.1%
2 10
 
6.4%
9 9
 
5.8%
4 8
 
5.1%
6 8
 
5.1%
8 6
 
3.8%
5 3
 
1.9%

ambulatory_surgical_center
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing999
Missing (%)99.9%
Memory size31.4 KiB
2023-12-09T23:28:48.871008image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters6
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row238000
ValueCountFrequency (%)
238000 1
100.0%
2023-12-09T23:28:49.131731image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3
50.0%
2 1
 
16.7%
3 1
 
16.7%
8 1
 
16.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3
50.0%
2 1
 
16.7%
3 1
 
16.7%
8 1
 
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 6
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3
50.0%
2 1
 
16.7%
3 1
 
16.7%
8 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3
50.0%
2 1
 
16.7%
3 1
 
16.7%
8 1
 
16.7%

automobile_dealership_gross
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1000
Missing (%)100.0%
Memory size7.9 KiB
Distinct15
Distinct (%)75.0%
Missing980
Missing (%)98.0%
Memory size31.9 KiB
2023-12-09T23:28:49.323391image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.2
Min length1

Characters and Unicode

Total characters84
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)55.0%

Sample

1st row4662
2nd row32063
3rd row4404
4th row33785
5th row7296
ValueCountFrequency (%)
33785 3
15.0%
32063 2
 
10.0%
2579 2
 
10.0%
7296 2
 
10.0%
4404 1
 
5.0%
9144 1
 
5.0%
10000 1
 
5.0%
3000 1
 
5.0%
8548 1
 
5.0%
4662 1
 
5.0%
Other values (5) 5
25.0%
2023-12-09T23:28:49.672019image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 15
17.9%
3 13
15.5%
7 9
10.7%
2 9
10.7%
6 9
10.7%
4 8
9.5%
5 6
 
7.1%
9 6
 
7.1%
8 5
 
6.0%
1 4
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 84
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 15
17.9%
3 13
15.5%
7 9
10.7%
2 9
10.7%
6 9
10.7%
4 8
9.5%
5 6
 
7.1%
9 6
 
7.1%
8 5
 
6.0%
1 4
 
4.8%

Most occurring scripts

ValueCountFrequency (%)
Common 84
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 15
17.9%
3 13
15.5%
7 9
10.7%
2 9
10.7%
6 9
10.7%
4 8
9.5%
5 6
 
7.1%
9 6
 
7.1%
8 5
 
6.0%
1 4
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 84
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 15
17.9%
3 13
15.5%
7 9
10.7%
2 9
10.7%
6 9
10.7%
4 8
9.5%
5 6
 
7.1%
9 6
 
7.1%
8 5
 
6.0%
1 4
 
4.8%

bank_branch_number_of
Text

MISSING 

Distinct11
Distinct (%)55.0%
Missing980
Missing (%)98.0%
Memory size31.9 KiB
2023-12-09T23:28:49.860933image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length1.8
Min length1

Characters and Unicode

Total characters36
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)30.0%

Sample

1st row14
2nd row28
3rd row15
4th row36
5th row20
ValueCountFrequency (%)
14 3
15.0%
20 3
15.0%
0 3
15.0%
36 3
15.0%
28 2
10.0%
19 1
 
5.0%
15 1
 
5.0%
13 1
 
5.0%
17 1
 
5.0%
24 1
 
5.0%
2023-12-09T23:28:50.177801image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 7
19.4%
2 6
16.7%
0 6
16.7%
4 4
11.1%
3 4
11.1%
6 3
8.3%
8 3
8.3%
9 1
 
2.8%
5 1
 
2.8%
7 1
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 36
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 7
19.4%
2 6
16.7%
0 6
16.7%
4 4
11.1%
3 4
11.1%
6 3
8.3%
8 3
8.3%
9 1
 
2.8%
5 1
 
2.8%
7 1
 
2.8%

Most occurring scripts

ValueCountFrequency (%)
Common 36
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 7
19.4%
2 6
16.7%
0 6
16.7%
4 4
11.1%
3 4
11.1%
6 3
8.3%
8 3
8.3%
9 1
 
2.8%
5 1
 
2.8%
7 1
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 36
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 7
19.4%
2 6
16.7%
0 6
16.7%
4 4
11.1%
3 4
11.1%
6 3
8.3%
8 3
8.3%
9 1
 
2.8%
5 1
 
2.8%
7 1
 
2.8%
Distinct18
Distinct (%)81.8%
Missing978
Missing (%)97.8%
Memory size32.0 KiB
2023-12-09T23:28:50.385644image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.318181818
Min length5

Characters and Unicode

Total characters117
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)72.7%

Sample

1st row39905
2nd row25984
3rd row51389
4th row26260
5th row40000
ValueCountFrequency (%)
40000 3
 
13.6%
83267 3
 
13.6%
59675 1
 
4.5%
25984 1
 
4.5%
253942 1
 
4.5%
105698 1
 
4.5%
39905 1
 
4.5%
102095 1
 
4.5%
26260 1
 
4.5%
72187 1
 
4.5%
Other values (8) 8
36.4%
2023-12-09T23:28:50.720609image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 22
18.8%
5 15
12.8%
2 14
12.0%
7 13
11.1%
9 11
9.4%
1 10
8.5%
6 9
7.7%
8 8
 
6.8%
3 8
 
6.8%
4 7
 
6.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 117
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 22
18.8%
5 15
12.8%
2 14
12.0%
7 13
11.1%
9 11
9.4%
1 10
8.5%
6 9
7.7%
8 8
 
6.8%
3 8
 
6.8%
4 7
 
6.0%

Most occurring scripts

ValueCountFrequency (%)
Common 117
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 22
18.8%
5 15
12.8%
2 14
12.0%
7 13
11.1%
9 11
9.4%
1 10
8.5%
6 9
7.7%
8 8
 
6.8%
3 8
 
6.8%
4 7
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 117
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 22
18.8%
5 15
12.8%
2 14
12.0%
7 13
11.1%
9 11
9.4%
1 10
8.5%
6 9
7.7%
8 8
 
6.8%
3 8
 
6.8%
4 7
 
6.0%
Distinct9
Distinct (%)64.3%
Missing986
Missing (%)98.6%
Memory size31.8 KiB
2023-12-09T23:28:50.903400image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.642857143
Min length1

Characters and Unicode

Total characters37
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)42.9%

Sample

1st row10
2nd row0
3rd row0
4th row100
5th row190
ValueCountFrequency (%)
190 3
21.4%
100 3
21.4%
0 2
14.3%
10 1
 
7.1%
1000 1
 
7.1%
132 1
 
7.1%
30 1
 
7.1%
500 1
 
7.1%
200 1
 
7.1%
2023-12-09T23:28:51.201252image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 20
54.1%
1 9
24.3%
9 3
 
8.1%
3 2
 
5.4%
2 2
 
5.4%
5 1
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 37
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 20
54.1%
1 9
24.3%
9 3
 
8.1%
3 2
 
5.4%
2 2
 
5.4%
5 1
 
2.7%

Most occurring scripts

ValueCountFrequency (%)
Common 37
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 20
54.1%
1 9
24.3%
9 3
 
8.1%
3 2
 
5.4%
2 2
 
5.4%
5 1
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 37
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 20
54.1%
1 9
24.3%
9 3
 
8.1%
3 2
 
5.4%
2 2
 
5.4%
5 1
 
2.7%

convention_center_gross_floor
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1000
Missing (%)100.0%
Memory size7.9 KiB

courthouse_gross_floor_area
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1000
Missing (%)100.0%
Memory size7.9 KiB
Distinct6
Distinct (%)100.0%
Missing994
Missing (%)99.4%
Memory size31.5 KiB
2023-12-09T23:28:51.390358image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.333333333
Min length4

Characters and Unicode

Total characters26
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st row1071
2nd row3181
3rd row3901
4th row4368
5th row33176
ValueCountFrequency (%)
3901 1
16.7%
3181 1
16.7%
4368 1
16.7%
33176 1
16.7%
1071 1
16.7%
21126 1
16.7%
2023-12-09T23:28:51.700914image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 8
30.8%
3 5
19.2%
6 3
 
11.5%
0 2
 
7.7%
8 2
 
7.7%
7 2
 
7.7%
2 2
 
7.7%
9 1
 
3.8%
4 1
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 26
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 8
30.8%
3 5
19.2%
6 3
 
11.5%
0 2
 
7.7%
8 2
 
7.7%
7 2
 
7.7%
2 2
 
7.7%
9 1
 
3.8%
4 1
 
3.8%

Most occurring scripts

ValueCountFrequency (%)
Common 26
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 8
30.8%
3 5
19.2%
6 3
 
11.5%
0 2
 
7.7%
8 2
 
7.7%
7 2
 
7.7%
2 2
 
7.7%
9 1
 
3.8%
4 1
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 26
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 8
30.8%
3 5
19.2%
6 3
 
11.5%
0 2
 
7.7%
8 2
 
7.7%
7 2
 
7.7%
2 2
 
7.7%
9 1
 
3.8%
4 1
 
3.8%

data_center_pdu_input_meter
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)16.7%
Missing994
Missing (%)99.4%
Memory size31.5 KiB
2023-12-09T23:28:51.804781image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters6
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 6
100.0%
2023-12-09T23:28:52.015163image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6
100.0%

data_center_pdu_output_meter
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)16.7%
Missing994
Missing (%)99.4%
Memory size31.5 KiB
2023-12-09T23:28:52.116297image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters6
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 6
100.0%
2023-12-09T23:28:52.332050image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6
100.0%

data_center_it_equipment
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)16.7%
Missing994
Missing (%)99.4%
Memory size31.5 KiB
2023-12-09T23:28:52.434756image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters6
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 6
100.0%
2023-12-09T23:28:52.669692image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6
100.0%
Distinct5
Distinct (%)100.0%
Missing995
Missing (%)99.5%
Memory size31.5 KiB
2023-12-09T23:28:52.850149image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length10
Median length8
Mean length7.4
Min length6

Characters and Unicode

Total characters37
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st row266172.2
2nd row802974
3rd row450872
4th row13514428.1
5th row3474801
ValueCountFrequency (%)
266172.2 1
20.0%
13514428.1 1
20.0%
450872 1
20.0%
3474801 1
20.0%
802974 1
20.0%
2023-12-09T23:28:53.164802image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 6
16.2%
4 6
16.2%
1 5
13.5%
7 4
10.8%
8 4
10.8%
0 3
8.1%
6 2
 
5.4%
. 2
 
5.4%
3 2
 
5.4%
5 2
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 35
94.6%
Other Punctuation 2
 
5.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 6
17.1%
4 6
17.1%
1 5
14.3%
7 4
11.4%
8 4
11.4%
0 3
8.6%
6 2
 
5.7%
3 2
 
5.7%
5 2
 
5.7%
9 1
 
2.9%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 37
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 6
16.2%
4 6
16.2%
1 5
13.5%
7 4
10.8%
8 4
10.8%
0 3
8.1%
6 2
 
5.4%
. 2
 
5.4%
3 2
 
5.4%
5 2
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 37
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 6
16.2%
4 6
16.2%
1 5
13.5%
7 4
10.8%
8 4
10.8%
0 3
8.1%
6 2
 
5.4%
. 2
 
5.4%
3 2
 
5.4%
5 2
 
5.4%
Distinct5
Distinct (%)100.0%
Missing995
Missing (%)99.5%
Memory size31.5 KiB
2023-12-09T23:28:53.357707image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length11
Median length10
Mean length9.2
Min length7

Characters and Unicode

Total characters46
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st row2851684
2nd row8602806.7
3rd row4830498.3
4th row144789258.6
5th row37227906.5
ValueCountFrequency (%)
4830498.3 1
20.0%
37227906.5 1
20.0%
144789258.6 1
20.0%
8602806.7 1
20.0%
2851684 1
20.0%
2023-12-09T23:28:53.682461image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 8
17.4%
4 5
10.9%
2 5
10.9%
6 5
10.9%
0 4
8.7%
. 4
8.7%
7 4
8.7%
3 3
 
6.5%
9 3
 
6.5%
5 3
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 42
91.3%
Other Punctuation 4
 
8.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 8
19.0%
4 5
11.9%
2 5
11.9%
6 5
11.9%
0 4
9.5%
7 4
9.5%
3 3
 
7.1%
9 3
 
7.1%
5 3
 
7.1%
1 2
 
4.8%
Other Punctuation
ValueCountFrequency (%)
. 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 46
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 8
17.4%
4 5
10.9%
2 5
10.9%
6 5
10.9%
0 4
8.7%
. 4
8.7%
7 4
8.7%
3 3
 
6.5%
9 3
 
6.5%
5 3
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 8
17.4%
4 5
10.9%
2 5
10.9%
6 5
10.9%
0 4
8.7%
. 4
8.7%
7 4
8.7%
3 3
 
6.5%
9 3
 
6.5%
5 3
 
6.5%

data_center_pue
Text

MISSING 

Distinct5
Distinct (%)100.0%
Missing995
Missing (%)99.5%
Memory size31.5 KiB
2023-12-09T23:28:53.861803image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.2
Min length3

Characters and Unicode

Total characters21
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st row12.7
2nd row14.67
3rd row10.08
4th row1.8
5th row5.31
ValueCountFrequency (%)
10.08 1
20.0%
14.67 1
20.0%
5.31 1
20.0%
1.8 1
20.0%
12.7 1
20.0%
2023-12-09T23:28:54.171663image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 5
23.8%
. 5
23.8%
0 2
 
9.5%
8 2
 
9.5%
7 2
 
9.5%
4 1
 
4.8%
6 1
 
4.8%
5 1
 
4.8%
3 1
 
4.8%
2 1
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16
76.2%
Other Punctuation 5
 
23.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 5
31.2%
0 2
 
12.5%
8 2
 
12.5%
7 2
 
12.5%
4 1
 
6.2%
6 1
 
6.2%
5 1
 
6.2%
3 1
 
6.2%
2 1
 
6.2%
Other Punctuation
ValueCountFrequency (%)
. 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 21
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 5
23.8%
. 5
23.8%
0 2
 
9.5%
8 2
 
9.5%
7 2
 
9.5%
4 1
 
4.8%
6 1
 
4.8%
5 1
 
4.8%
3 1
 
4.8%
2 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 5
23.8%
. 5
23.8%
0 2
 
9.5%
8 2
 
9.5%
7 2
 
9.5%
4 1
 
4.8%
6 1
 
4.8%
5 1
 
4.8%
3 1
 
4.8%
2 1
 
4.8%

data_center_national_median
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1000
Missing (%)100.0%
Memory size7.9 KiB
Distinct6
Distinct (%)100.0%
Missing994
Missing (%)99.4%
Memory size31.6 KiB
2023-12-09T23:28:54.351913image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length10
Median length7.5
Mean length6.333333333
Min length1

Characters and Unicode

Total characters38
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st row266172.2
2nd row802974
3rd row0
4th row450872
5th row13514428.1
ValueCountFrequency (%)
266172.2 1
16.7%
13514428.1 1
16.7%
450872 1
16.7%
3474801 1
16.7%
0 1
16.7%
802974 1
16.7%
2023-12-09T23:28:54.647194image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 6
15.8%
4 6
15.8%
1 5
13.2%
7 4
10.5%
8 4
10.5%
0 4
10.5%
6 2
 
5.3%
. 2
 
5.3%
3 2
 
5.3%
5 2
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 36
94.7%
Other Punctuation 2
 
5.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 6
16.7%
4 6
16.7%
1 5
13.9%
7 4
11.1%
8 4
11.1%
0 4
11.1%
6 2
 
5.6%
3 2
 
5.6%
5 2
 
5.6%
9 1
 
2.8%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 38
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 6
15.8%
4 6
15.8%
1 5
13.2%
7 4
10.5%
8 4
10.5%
0 4
10.5%
6 2
 
5.3%
. 2
 
5.3%
3 2
 
5.3%
5 2
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 38
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 6
15.8%
4 6
15.8%
1 5
13.2%
7 4
10.5%
8 4
10.5%
0 4
10.5%
6 2
 
5.3%
. 2
 
5.3%
3 2
 
5.3%
5 2
 
5.3%
Distinct2
Distinct (%)100.0%
Missing998
Missing (%)99.8%
Memory size31.4 KiB
2023-12-09T23:28:54.770870image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length4.5
Mean length4.5
Min length3

Characters and Unicode

Total characters9
Distinct characters5
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowN+1
2nd rowN+1, N
ValueCountFrequency (%)
n+1 2
66.7%
n 1
33.3%
2023-12-09T23:28:55.010834image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 3
33.3%
+ 2
22.2%
1 2
22.2%
, 1
 
11.1%
1
 
11.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 3
33.3%
Math Symbol 2
22.2%
Decimal Number 2
22.2%
Other Punctuation 1
 
11.1%
Space Separator 1
 
11.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 3
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%
Decimal Number
ValueCountFrequency (%)
1 2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6
66.7%
Latin 3
33.3%

Most frequent character per script

Common
ValueCountFrequency (%)
+ 2
33.3%
1 2
33.3%
, 1
16.7%
1
16.7%
Latin
ValueCountFrequency (%)
N 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 3
33.3%
+ 2
22.2%
1 2
22.2%
, 1
 
11.1%
1
 
11.1%

data_center_it_energy
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)16.7%
Missing994
Missing (%)99.4%
Memory size31.9 KiB
2023-12-09T23:28:55.197402image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length73
Median length73
Mean length73
Min length73

Characters and Unicode

Total characters438
Distinct characters26
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUninterruptible Power Supply (UPS) supports only IT Equipment (preferred)
2nd rowUninterruptible Power Supply (UPS) supports only IT Equipment (preferred)
3rd rowUninterruptible Power Supply (UPS) supports only IT Equipment (preferred)
4th rowUninterruptible Power Supply (UPS) supports only IT Equipment (preferred)
5th rowUninterruptible Power Supply (UPS) supports only IT Equipment (preferred)
ValueCountFrequency (%)
uninterruptible 6
11.1%
power 6
11.1%
supply 6
11.1%
ups 6
11.1%
supports 6
11.1%
only 6
11.1%
it 6
11.1%
equipment 6
11.1%
preferred 6
11.1%
2023-12-09T23:28:55.502449image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
48
 
11.0%
e 42
 
9.6%
r 42
 
9.6%
p 42
 
9.6%
t 24
 
5.5%
u 24
 
5.5%
n 24
 
5.5%
i 18
 
4.1%
l 18
 
4.1%
o 18
 
4.1%
Other values (16) 138
31.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 312
71.2%
Uppercase Letter 54
 
12.3%
Space Separator 48
 
11.0%
Close Punctuation 12
 
2.7%
Open Punctuation 12
 
2.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 42
13.5%
r 42
13.5%
p 42
13.5%
t 24
7.7%
u 24
7.7%
n 24
7.7%
i 18
 
5.8%
l 18
 
5.8%
o 18
 
5.8%
y 12
 
3.8%
Other values (7) 48
15.4%
Uppercase Letter
ValueCountFrequency (%)
U 12
22.2%
S 12
22.2%
P 12
22.2%
E 6
11.1%
T 6
11.1%
I 6
11.1%
Space Separator
ValueCountFrequency (%)
48
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 366
83.6%
Common 72
 
16.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 42
11.5%
r 42
11.5%
p 42
11.5%
t 24
 
6.6%
u 24
 
6.6%
n 24
 
6.6%
i 18
 
4.9%
l 18
 
4.9%
o 18
 
4.9%
y 12
 
3.3%
Other values (13) 102
27.9%
Common
ValueCountFrequency (%)
48
66.7%
) 12
 
16.7%
( 12
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 438
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
48
 
11.0%
e 42
 
9.6%
r 42
 
9.6%
p 42
 
9.6%
t 24
 
5.5%
u 24
 
5.5%
n 24
 
5.5%
i 18
 
4.1%
l 18
 
4.1%
o 18
 
4.1%
Other values (16) 138
31.5%
Distinct2
Distinct (%)100.0%
Missing998
Missing (%)99.8%
Memory size31.4 KiB
2023-12-09T23:28:55.622733image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length4.5
Mean length4.5
Min length3

Characters and Unicode

Total characters9
Distinct characters5
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowN+1
2nd rowN+1, N
ValueCountFrequency (%)
n+1 2
66.7%
n 1
33.3%
2023-12-09T23:28:55.863471image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 3
33.3%
+ 2
22.2%
1 2
22.2%
, 1
 
11.1%
1
 
11.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 3
33.3%
Math Symbol 2
22.2%
Decimal Number 2
22.2%
Other Punctuation 1
 
11.1%
Space Separator 1
 
11.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 3
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%
Decimal Number
ValueCountFrequency (%)
1 2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6
66.7%
Latin 3
33.3%

Most frequent character per script

Common
ValueCountFrequency (%)
+ 2
33.3%
1 2
33.3%
, 1
16.7%
1
16.7%
Latin
ValueCountFrequency (%)
N 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 3
33.3%
+ 2
22.2%
1 2
22.2%
, 1
 
11.1%
1
 
11.1%
Distinct12
Distinct (%)92.3%
Missing987
Missing (%)98.7%
Memory size31.8 KiB
2023-12-09T23:28:56.039660image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.307692308
Min length5

Characters and Unicode

Total characters69
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)84.6%

Sample

1st row200000
2nd row190000
3rd row340000
4th row88000
5th row88000
ValueCountFrequency (%)
88000 2
15.4%
60376 1
7.7%
27920 1
7.7%
200000 1
7.7%
207000 1
7.7%
53660 1
7.7%
37201 1
7.7%
30000 1
7.7%
68000 1
7.7%
13125 1
7.7%
Other values (2) 2
15.4%
2023-12-09T23:28:56.343534image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 34
49.3%
3 6
 
8.7%
2 6
 
8.7%
8 5
 
7.2%
6 5
 
7.2%
7 4
 
5.8%
1 4
 
5.8%
9 2
 
2.9%
5 2
 
2.9%
4 1
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 69
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 34
49.3%
3 6
 
8.7%
2 6
 
8.7%
8 5
 
7.2%
6 5
 
7.2%
7 4
 
5.8%
1 4
 
5.8%
9 2
 
2.9%
5 2
 
2.9%
4 1
 
1.4%

Most occurring scripts

ValueCountFrequency (%)
Common 69
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 34
49.3%
3 6
 
8.7%
2 6
 
8.7%
8 5
 
7.2%
6 5
 
7.2%
7 4
 
5.8%
1 4
 
5.8%
9 2
 
2.9%
5 2
 
2.9%
4 1
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 69
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 34
49.3%
3 6
 
8.7%
2 6
 
8.7%
8 5
 
7.2%
6 5
 
7.2%
7 4
 
5.8%
1 4
 
5.8%
9 2
 
2.9%
5 2
 
2.9%
4 1
 
1.4%

enclosed_mall_gross_floor
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)50.0%
Missing998
Missing (%)99.8%
Memory size31.4 KiB
2023-12-09T23:28:57.109093image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters8
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row9969
2nd row9969
ValueCountFrequency (%)
9969 2
100.0%
2023-12-09T23:28:57.344857image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 6
75.0%
6 2
 
25.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 6
75.0%
6 2
 
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
9 6
75.0%
6 2
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 6
75.0%
6 2
 
25.0%

energy_power_station_gross
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1000
Missing (%)100.0%
Memory size7.9 KiB
Distinct17
Distinct (%)85.0%
Missing980
Missing (%)98.0%
Memory size31.9 KiB
2023-12-09T23:28:57.530934image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.4
Min length1

Characters and Unicode

Total characters88
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)75.0%

Sample

1st row4339
2nd row4339
3rd row94639
4th row4339
5th row9300
ValueCountFrequency (%)
4339 3
15.0%
0 2
 
10.0%
5000 1
 
5.0%
17292 1
 
5.0%
72740 1
 
5.0%
9300 1
 
5.0%
679149 1
 
5.0%
273124 1
 
5.0%
5586 1
 
5.0%
94639 1
 
5.0%
Other values (7) 7
35.0%
2023-12-09T23:28:57.847998image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
12.5%
2 11
12.5%
4 10
11.4%
3 10
11.4%
9 10
11.4%
7 10
11.4%
1 8
9.1%
5 8
9.1%
6 5
5.7%
8 5
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 88
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
12.5%
2 11
12.5%
4 10
11.4%
3 10
11.4%
9 10
11.4%
7 10
11.4%
1 8
9.1%
5 8
9.1%
6 5
5.7%
8 5
5.7%

Most occurring scripts

ValueCountFrequency (%)
Common 88
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
12.5%
2 11
12.5%
4 10
11.4%
3 10
11.4%
9 10
11.4%
7 10
11.4%
1 8
9.1%
5 8
9.1%
6 5
5.7%
8 5
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 88
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
12.5%
2 11
12.5%
4 10
11.4%
3 10
11.4%
9 10
11.4%
7 10
11.4%
1 8
9.1%
5 8
9.1%
6 5
5.7%
8 5
5.7%
Distinct17
Distinct (%)85.0%
Missing980
Missing (%)98.0%
Memory size31.9 KiB
2023-12-09T23:28:58.046342image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length4.5
Mean length2.6
Min length1

Characters and Unicode

Total characters52
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)75.0%

Sample

1st row10
2nd row10
3rd row408
4th row10
5th row15
ValueCountFrequency (%)
10 3
15.0%
0 2
 
10.0%
43 1
 
5.0%
15 1
 
5.0%
1550 1
 
5.0%
2461 1
 
5.0%
17 1
 
5.0%
250 1
 
5.0%
22 1
 
5.0%
8.2 1
 
5.0%
Other values (7) 7
35.0%
2023-12-09T23:28:58.382696image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 11
21.2%
0 11
21.2%
2 9
17.3%
5 6
11.5%
3 4
 
7.7%
4 3
 
5.8%
7 3
 
5.8%
8 2
 
3.8%
. 2
 
3.8%
6 1
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 50
96.2%
Other Punctuation 2
 
3.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 11
22.0%
0 11
22.0%
2 9
18.0%
5 6
12.0%
3 4
 
8.0%
4 3
 
6.0%
7 3
 
6.0%
8 2
 
4.0%
6 1
 
2.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 52
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 11
21.2%
0 11
21.2%
2 9
17.3%
5 6
11.5%
3 4
 
7.7%
4 3
 
5.8%
7 3
 
5.8%
8 2
 
3.8%
. 2
 
3.8%
6 1
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 52
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 11
21.2%
0 11
21.2%
2 9
17.3%
5 6
11.5%
3 4
 
7.7%
4 3
 
5.8%
7 3
 
5.8%
8 2
 
3.8%
. 2
 
3.8%
6 1
 
1.9%
Distinct15
Distinct (%)75.0%
Missing980
Missing (%)98.0%
Memory size31.9 KiB
2023-12-09T23:28:58.562031image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.55
Min length1

Characters and Unicode

Total characters51
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)65.0%

Sample

1st row10
2nd row10
3rd row277
4th row10
5th row10
ValueCountFrequency (%)
10 5
25.0%
0 2
 
10.0%
40.31 1
 
5.0%
2129 1
 
5.0%
909 1
 
5.0%
1371 1
 
5.0%
26 1
 
5.0%
8 1
 
5.0%
277 1
 
5.0%
20 1
 
5.0%
Other values (5) 5
25.0%
2023-12-09T23:28:58.869462image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
21.6%
1 9
17.6%
2 9
17.6%
3 6
11.8%
9 5
9.8%
7 4
 
7.8%
4 2
 
3.9%
. 2
 
3.9%
6 2
 
3.9%
8 1
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 49
96.1%
Other Punctuation 2
 
3.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
22.4%
1 9
18.4%
2 9
18.4%
3 6
12.2%
9 5
10.2%
7 4
 
8.2%
4 2
 
4.1%
6 2
 
4.1%
8 1
 
2.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 51
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
21.6%
1 9
17.6%
2 9
17.6%
3 6
11.8%
9 5
9.8%
7 4
 
7.8%
4 2
 
3.9%
. 2
 
3.9%
6 2
 
3.9%
8 1
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 51
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
21.6%
1 9
17.6%
2 9
17.6%
3 6
11.8%
9 5
9.8%
7 4
 
7.8%
4 2
 
3.9%
. 2
 
3.9%
6 2
 
3.9%
8 1
 
2.0%
Distinct14
Distinct (%)70.0%
Missing980
Missing (%)98.0%
Memory size31.9 KiB
2023-12-09T23:28:59.047942image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length2
Mean length2.3
Min length1

Characters and Unicode

Total characters46
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)55.0%

Sample

1st row42.5
2nd row42.5
3rd row55
4th row42.5
5th row42
ValueCountFrequency (%)
65 4
20.0%
42.5 3
15.0%
0 2
10.0%
54 1
 
5.0%
57 1
 
5.0%
70 1
 
5.0%
90 1
 
5.0%
84 1
 
5.0%
42 1
 
5.0%
54.4 1
 
5.0%
Other values (4) 4
20.0%
2023-12-09T23:28:59.368670image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 14
30.4%
4 8
17.4%
6 6
13.0%
2 5
 
10.9%
. 4
 
8.7%
0 4
 
8.7%
7 2
 
4.3%
9 1
 
2.2%
8 1
 
2.2%
3 1
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 42
91.3%
Other Punctuation 4
 
8.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 14
33.3%
4 8
19.0%
6 6
14.3%
2 5
 
11.9%
0 4
 
9.5%
7 2
 
4.8%
9 1
 
2.4%
8 1
 
2.4%
3 1
 
2.4%
Other Punctuation
ValueCountFrequency (%)
. 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 46
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 14
30.4%
4 8
17.4%
6 6
13.0%
2 5
 
10.9%
. 4
 
8.7%
0 4
 
8.7%
7 2
 
4.3%
9 1
 
2.2%
8 1
 
2.2%
3 1
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 14
30.4%
4 8
17.4%
6 6
13.0%
2 5
 
10.9%
. 4
 
8.7%
0 4
 
8.7%
7 2
 
4.3%
9 1
 
2.2%
8 1
 
2.2%
3 1
 
2.2%
Distinct7
Distinct (%)87.5%
Missing992
Missing (%)99.2%
Memory size31.6 KiB
2023-12-09T23:28:59.540913image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.875
Min length4

Characters and Unicode

Total characters39
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)75.0%

Sample

1st row34000
2nd row15700
3rd row15700
4th row25913
5th row31169
ValueCountFrequency (%)
15700 2
25.0%
34000 1
12.5%
31169 1
12.5%
25913 1
12.5%
14500 1
12.5%
29300 1
12.5%
7500 1
12.5%
2023-12-09T23:28:59.830274image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
33.3%
1 6
15.4%
5 5
 
12.8%
3 4
 
10.3%
7 3
 
7.7%
9 3
 
7.7%
4 2
 
5.1%
2 2
 
5.1%
6 1
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 39
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13
33.3%
1 6
15.4%
5 5
 
12.8%
3 4
 
10.3%
7 3
 
7.7%
9 3
 
7.7%
4 2
 
5.1%
2 2
 
5.1%
6 1
 
2.6%

Most occurring scripts

ValueCountFrequency (%)
Common 39
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 13
33.3%
1 6
15.4%
5 5
 
12.8%
3 4
 
10.3%
7 3
 
7.7%
9 3
 
7.7%
4 2
 
5.1%
2 2
 
5.1%
6 1
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 39
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13
33.3%
1 6
15.4%
5 5
 
12.8%
3 4
 
10.3%
7 3
 
7.7%
9 3
 
7.7%
4 2
 
5.1%
2 2
 
5.1%
6 1
 
2.6%
Distinct5
Distinct (%)83.3%
Missing994
Missing (%)99.4%
Memory size31.5 KiB
2023-12-09T23:28:59.991064image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.166666667
Min length4

Characters and Unicode

Total characters25
Distinct characters8
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)66.7%

Sample

1st row355.6
2nd row5000
3rd row5000
4th row2500
5th row6470
ValueCountFrequency (%)
5000 2
33.3%
2763 1
16.7%
6470 1
16.7%
2500 1
16.7%
355.6 1
16.7%
2023-12-09T23:29:00.269839image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9
36.0%
5 5
20.0%
6 3
 
12.0%
2 2
 
8.0%
7 2
 
8.0%
3 2
 
8.0%
4 1
 
4.0%
. 1
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 24
96.0%
Other Punctuation 1
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9
37.5%
5 5
20.8%
6 3
 
12.5%
2 2
 
8.3%
7 2
 
8.3%
3 2
 
8.3%
4 1
 
4.2%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 25
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9
36.0%
5 5
20.0%
6 3
 
12.0%
2 2
 
8.0%
7 2
 
8.0%
3 2
 
8.0%
4 1
 
4.0%
. 1
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9
36.0%
5 5
20.0%
6 3
 
12.0%
2 2
 
8.0%
7 2
 
8.0%
3 2
 
8.0%
4 1
 
4.0%
. 1
 
4.0%
Distinct2
Distinct (%)66.7%
Missing997
Missing (%)99.7%
Memory size31.5 KiB
2023-12-09T23:29:00.417627image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters15
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)33.3%

Sample

1st row55000
2nd row55000
3rd row12857
ValueCountFrequency (%)
55000 2
66.7%
12857 1
33.3%
2023-12-09T23:29:00.680011image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6
40.0%
5 5
33.3%
1 1
 
6.7%
2 1
 
6.7%
8 1
 
6.7%
7 1
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6
40.0%
5 5
33.3%
1 1
 
6.7%
2 1
 
6.7%
8 1
 
6.7%
7 1
 
6.7%

Most occurring scripts

ValueCountFrequency (%)
Common 15
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6
40.0%
5 5
33.3%
1 1
 
6.7%
2 1
 
6.7%
8 1
 
6.7%
7 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6
40.0%
5 5
33.3%
1 1
 
6.7%
2 1
 
6.7%
8 1
 
6.7%
7 1
 
6.7%
Distinct13
Distinct (%)92.9%
Missing986
Missing (%)98.6%
Memory size31.8 KiB
2023-12-09T23:29:00.861408image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5
Min length3

Characters and Unicode

Total characters70
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)85.7%

Sample

1st row167.96
2nd row759.8
3rd row448
4th row167.96
5th row178.85
ValueCountFrequency (%)
167.96 2
14.3%
3366 1
 
7.1%
6405 1
 
7.1%
759.8 1
 
7.1%
212.19 1
 
7.1%
1016.54 1
 
7.1%
178.85 1
 
7.1%
450 1
 
7.1%
196.56 1
 
7.1%
3550 1
 
7.1%
Other values (3) 3
21.4%
2023-12-09T23:29:01.183681image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
17.1%
6 10
14.3%
. 8
11.4%
5 8
11.4%
9 6
8.6%
4 6
8.6%
7 5
7.1%
0 5
7.1%
8 4
 
5.7%
3 3
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 62
88.6%
Other Punctuation 8
 
11.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 12
19.4%
6 10
16.1%
5 8
12.9%
9 6
9.7%
4 6
9.7%
7 5
8.1%
0 5
8.1%
8 4
 
6.5%
3 3
 
4.8%
2 3
 
4.8%
Other Punctuation
ValueCountFrequency (%)
. 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 70
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 12
17.1%
6 10
14.3%
. 8
11.4%
5 8
11.4%
9 6
8.6%
4 6
8.6%
7 5
7.1%
0 5
7.1%
8 4
 
5.7%
3 3
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 70
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 12
17.1%
6 10
14.3%
. 8
11.4%
5 8
11.4%
9 6
8.6%
4 6
8.6%
7 5
7.1%
0 5
7.1%
8 4
 
5.7%
3 3
 
4.3%
Distinct7
Distinct (%)50.0%
Missing986
Missing (%)98.6%
Memory size31.8 KiB
2023-12-09T23:29:01.345356image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length3
Mean length4.642857143
Min length3

Characters and Unicode

Total characters65
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)42.9%

Sample

1st row2.6
2nd row2.6
3rd row2.6006
4th row2.6
5th row2.6
ValueCountFrequency (%)
2.6 8
57.1%
6.01317 1
 
7.1%
4.28833 1
 
7.1%
2.6006 1
 
7.1%
2.61963 1
 
7.1%
6.00731 1
 
7.1%
3.85567 1
 
7.1%
2023-12-09T23:29:01.637049image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 15
23.1%
. 14
21.5%
2 11
16.9%
3 6
 
9.2%
0 5
 
7.7%
1 4
 
6.2%
7 3
 
4.6%
8 3
 
4.6%
5 2
 
3.1%
4 1
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 51
78.5%
Other Punctuation 14
 
21.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 15
29.4%
2 11
21.6%
3 6
 
11.8%
0 5
 
9.8%
1 4
 
7.8%
7 3
 
5.9%
8 3
 
5.9%
5 2
 
3.9%
4 1
 
2.0%
9 1
 
2.0%
Other Punctuation
ValueCountFrequency (%)
. 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 65
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 15
23.1%
. 14
21.5%
2 11
16.9%
3 6
 
9.2%
0 5
 
7.7%
1 4
 
6.2%
7 3
 
4.6%
8 3
 
4.6%
5 2
 
3.1%
4 1
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 65
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 15
23.1%
. 14
21.5%
2 11
16.9%
3 6
 
9.2%
0 5
 
7.7%
1 4
 
6.2%
7 3
 
4.6%
8 3
 
4.6%
5 2
 
3.1%
4 1
 
1.5%
Distinct13
Distinct (%)92.9%
Missing986
Missing (%)98.6%
Memory size31.8 KiB
2023-12-09T23:29:01.842383image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length6.5
Mean length5.642857143
Min length5

Characters and Unicode

Total characters79
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)85.7%

Sample

1st row64600
2nd row292230
3rd row172268
4th row64600
5th row68787
ValueCountFrequency (%)
64600 2
14.3%
80844 1
 
7.1%
873000 1
 
7.1%
68787 1
 
7.1%
390975 1
 
7.1%
75600 1
 
7.1%
172268 1
 
7.1%
81613 1
 
7.1%
1493589 1
 
7.1%
171780 1
 
7.1%
Other values (3) 3
21.4%
2023-12-09T23:29:02.206118image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 15
19.0%
8 9
11.4%
7 9
11.4%
6 8
10.1%
9 8
10.1%
1 8
10.1%
3 7
8.9%
4 6
 
7.6%
2 5
 
6.3%
5 4
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 79
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 15
19.0%
8 9
11.4%
7 9
11.4%
6 8
10.1%
9 8
10.1%
1 8
10.1%
3 7
8.9%
4 6
 
7.6%
2 5
 
6.3%
5 4
 
5.1%

Most occurring scripts

ValueCountFrequency (%)
Common 79
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 15
19.0%
8 9
11.4%
7 9
11.4%
6 8
10.1%
9 8
10.1%
1 8
10.1%
3 7
8.9%
4 6
 
7.6%
2 5
 
6.3%
5 4
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 79
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 15
19.0%
8 9
11.4%
7 9
11.4%
6 8
10.1%
9 8
10.1%
1 8
10.1%
3 7
8.9%
4 6
 
7.6%
2 5
 
6.3%
5 4
 
5.1%
Distinct2
Distinct (%)16.7%
Missing988
Missing (%)98.8%
Memory size31.7 KiB
2023-12-09T23:29:02.359943image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length8
Median length2
Mean length4
Min length2

Characters and Unicode

Total characters48
Distinct characters9
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 8
50.0%
100 4
25.0%
yes 4
25.0%
2023-12-09T23:29:02.620947image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 8
16.7%
o 8
16.7%
0 8
16.7%
1 4
8.3%
% 4
8.3%
4
8.3%
Y 4
8.3%
e 4
8.3%
s 4
8.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 16
33.3%
Uppercase Letter 12
25.0%
Decimal Number 12
25.0%
Other Punctuation 4
 
8.3%
Space Separator 4
 
8.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 8
50.0%
e 4
25.0%
s 4
25.0%
Uppercase Letter
ValueCountFrequency (%)
N 8
66.7%
Y 4
33.3%
Decimal Number
ValueCountFrequency (%)
0 8
66.7%
1 4
33.3%
Other Punctuation
ValueCountFrequency (%)
% 4
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 28
58.3%
Common 20
41.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 8
28.6%
o 8
28.6%
Y 4
14.3%
e 4
14.3%
s 4
14.3%
Common
ValueCountFrequency (%)
0 8
40.0%
1 4
20.0%
% 4
20.0%
4
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 48
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 8
16.7%
o 8
16.7%
0 8
16.7%
1 4
8.3%
% 4
8.3%
4
8.3%
Y 4
8.3%
e 4
8.3%
s 4
8.3%
Distinct13
Distinct (%)92.9%
Missing986
Missing (%)98.6%
Memory size31.8 KiB
2023-12-09T23:29:02.800115image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.142857143
Min length3

Characters and Unicode

Total characters58
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)85.7%

Sample

1st row44.6
2nd row201.6
3rd row119
4th row44.6
5th row47.5
ValueCountFrequency (%)
44.6 2
14.3%
652 1
 
7.1%
52.2 1
 
7.1%
56.31 1
 
7.1%
119 1
 
7.1%
55.8 1
 
7.1%
201.6 1
 
7.1%
407.4 1
 
7.1%
269.77 1
 
7.1%
644 1
 
7.1%
Other values (3) 3
21.4%
2023-12-09T23:29:03.105160image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 10
17.2%
4 9
15.5%
6 7
12.1%
5 7
12.1%
1 7
12.1%
2 6
10.3%
7 4
 
6.9%
3 2
 
3.4%
9 2
 
3.4%
8 2
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 48
82.8%
Other Punctuation 10
 
17.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 9
18.8%
6 7
14.6%
5 7
14.6%
1 7
14.6%
2 6
12.5%
7 4
8.3%
3 2
 
4.2%
9 2
 
4.2%
8 2
 
4.2%
0 2
 
4.2%
Other Punctuation
ValueCountFrequency (%)
. 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 58
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 10
17.2%
4 9
15.5%
6 7
12.1%
5 7
12.1%
1 7
12.1%
2 6
10.3%
7 4
 
6.9%
3 2
 
3.4%
9 2
 
3.4%
8 2
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 58
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 10
17.2%
4 9
15.5%
6 7
12.1%
5 7
12.1%
1 7
12.1%
2 6
10.3%
7 4
 
6.9%
3 2
 
3.4%
9 2
 
3.4%
8 2
 
3.4%
Distinct12
Distinct (%)85.7%
Missing986
Missing (%)98.6%
Memory size31.8 KiB
2023-12-09T23:29:03.310481image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.428571429
Min length4

Characters and Unicode

Total characters90
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)71.4%

Sample

1st row0.6904
2nd row0.68987
3rd row0.69078
4th row0.6904
5th row0.69054
ValueCountFrequency (%)
0.69 2
14.3%
0.6904 2
14.3%
0.68984 1
7.1%
0.69022 1
7.1%
0.69007 1
7.1%
0.74685 1
7.1%
0.69054 1
7.1%
0.69048 1
7.1%
0.69078 1
7.1%
0.43118 1
7.1%
Other values (2) 2
14.3%
2023-12-09T23:29:03.648121image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 22
24.4%
. 14
15.6%
6 13
14.4%
9 11
12.2%
4 8
 
8.9%
8 8
 
8.9%
7 5
 
5.6%
1 3
 
3.3%
2 2
 
2.2%
5 2
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 76
84.4%
Other Punctuation 14
 
15.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 22
28.9%
6 13
17.1%
9 11
14.5%
4 8
 
10.5%
8 8
 
10.5%
7 5
 
6.6%
1 3
 
3.9%
2 2
 
2.6%
5 2
 
2.6%
3 2
 
2.6%
Other Punctuation
ValueCountFrequency (%)
. 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 90
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 22
24.4%
. 14
15.6%
6 13
14.4%
9 11
12.2%
4 8
 
8.9%
8 8
 
8.9%
7 5
 
5.6%
1 3
 
3.3%
2 2
 
2.2%
5 2
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 22
24.4%
. 14
15.6%
6 13
14.4%
9 11
12.2%
4 8
 
8.9%
8 8
 
8.9%
7 5
 
5.6%
1 3
 
3.3%
2 2
 
2.2%
5 2
 
2.2%
Distinct13
Distinct (%)92.9%
Missing986
Missing (%)98.6%
Memory size31.8 KiB
2023-12-09T23:29:03.847654image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.5
Min length1

Characters and Unicode

Total characters91
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)85.7%

Sample

1st row0.01548
2nd row0.00342
3rd row0.0058
4th row0.01548
5th row0.01454
ValueCountFrequency (%)
0.01548 2
14.3%
0.01225 1
 
7.1%
0.01237 1
 
7.1%
0.00342 1
 
7.1%
0.00134 1
 
7.1%
0.01323 1
 
7.1%
0.00524 1
 
7.1%
0.00256 1
 
7.1%
0.00229 1
 
7.1%
0.00339 1
 
7.1%
Other values (3) 3
21.4%
2023-12-09T23:29:04.167109image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 34
37.4%
. 13
 
14.3%
2 9
 
9.9%
1 7
 
7.7%
5 7
 
7.7%
4 7
 
7.7%
3 7
 
7.7%
8 3
 
3.3%
9 2
 
2.2%
7 1
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 78
85.7%
Other Punctuation 13
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 34
43.6%
2 9
 
11.5%
1 7
 
9.0%
5 7
 
9.0%
4 7
 
9.0%
3 7
 
9.0%
8 3
 
3.8%
9 2
 
2.6%
7 1
 
1.3%
6 1
 
1.3%
Other Punctuation
ValueCountFrequency (%)
. 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 91
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 34
37.4%
. 13
 
14.3%
2 9
 
9.9%
1 7
 
7.7%
5 7
 
7.7%
4 7
 
7.7%
3 7
 
7.7%
8 3
 
3.3%
9 2
 
2.2%
7 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 91
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 34
37.4%
. 13
 
14.3%
2 9
 
9.9%
1 7
 
7.7%
5 7
 
7.7%
4 7
 
7.7%
3 7
 
7.7%
8 3
 
3.3%
9 2
 
2.2%
7 1
 
1.1%
Distinct3
Distinct (%)21.4%
Missing986
Missing (%)98.6%
Memory size31.7 KiB
2023-12-09T23:29:04.299222image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters14
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)7.1%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
1 10
71.4%
2 3
 
21.4%
0 1
 
7.1%
2023-12-09T23:29:04.524030image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 10
71.4%
2 3
 
21.4%
0 1
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 10
71.4%
2 3
 
21.4%
0 1
 
7.1%

Most occurring scripts

ValueCountFrequency (%)
Common 14
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 10
71.4%
2 3
 
21.4%
0 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 10
71.4%
2 3
 
21.4%
0 1
 
7.1%
Distinct12
Distinct (%)85.7%
Missing986
Missing (%)98.6%
Memory size31.8 KiB
2023-12-09T23:29:04.718025image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.214285714
Min length2

Characters and Unicode

Total characters45
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)71.4%

Sample

1st row200
2nd row354
3rd row80
4th row200
5th row204
ValueCountFrequency (%)
80 2
14.3%
200 2
14.3%
354 1
7.1%
439 1
7.1%
235 1
7.1%
240 1
7.1%
314 1
7.1%
37.54 1
7.1%
644 1
7.1%
204 1
7.1%
Other values (2) 2
14.3%
2023-12-09T23:29:05.057849image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 8
17.8%
4 8
17.8%
2 6
13.3%
3 5
11.1%
5 5
11.1%
8 3
 
6.7%
9 2
 
4.4%
1 2
 
4.4%
7 2
 
4.4%
. 2
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 43
95.6%
Other Punctuation 2
 
4.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 8
18.6%
4 8
18.6%
2 6
14.0%
3 5
11.6%
5 5
11.6%
8 3
 
7.0%
9 2
 
4.7%
1 2
 
4.7%
7 2
 
4.7%
6 2
 
4.7%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 45
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 8
17.8%
4 8
17.8%
2 6
13.3%
3 5
11.1%
5 5
11.1%
8 3
 
6.7%
9 2
 
4.4%
1 2
 
4.4%
7 2
 
4.4%
. 2
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 45
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 8
17.8%
4 8
17.8%
2 6
13.3%
3 5
11.1%
5 5
11.1%
8 3
 
6.7%
9 2
 
4.4%
1 2
 
4.4%
7 2
 
4.4%
. 2
 
4.4%
Distinct10
Distinct (%)71.4%
Missing986
Missing (%)98.6%
Memory size31.8 KiB
2023-12-09T23:29:05.270561image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.571428571
Min length4

Characters and Unicode

Total characters92
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)42.9%

Sample

1st row1.32043
2nd row1.31985
3rd row1.31771
4th row1.32043
5th row1.32002
ValueCountFrequency (%)
1.32 2
14.3%
1.31983 2
14.3%
1.32002 2
14.3%
1.32043 2
14.3%
1.54754 1
7.1%
1.32011 1
7.1%
1.31771 1
7.1%
1.31985 1
7.1%
1.31971 1
7.1%
2.14249 1
7.1%
2023-12-09T23:29:05.593906image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 23
25.0%
3 16
17.4%
. 14
15.2%
2 11
12.0%
0 7
 
7.6%
4 6
 
6.5%
9 5
 
5.4%
7 4
 
4.3%
8 3
 
3.3%
5 3
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 78
84.8%
Other Punctuation 14
 
15.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 23
29.5%
3 16
20.5%
2 11
14.1%
0 7
 
9.0%
4 6
 
7.7%
9 5
 
6.4%
7 4
 
5.1%
8 3
 
3.8%
5 3
 
3.8%
Other Punctuation
ValueCountFrequency (%)
. 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 92
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 23
25.0%
3 16
17.4%
. 14
15.2%
2 11
12.0%
0 7
 
7.6%
4 6
 
6.5%
9 5
 
5.4%
7 4
 
4.3%
8 3
 
3.3%
5 3
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 92
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 23
25.0%
3 16
17.4%
. 14
15.2%
2 11
12.0%
0 7
 
7.6%
4 6
 
6.5%
9 5
 
5.4%
7 4
 
4.3%
8 3
 
3.3%
5 3
 
3.3%

hospital_general_medical_10
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)7.1%
Missing986
Missing (%)98.6%
Memory size31.8 KiB
2023-12-09T23:29:05.733456image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters42
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row100
2nd row100
3rd row100
4th row100
5th row100
ValueCountFrequency (%)
100 14
100.0%
2023-12-09T23:29:06.044456image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 28
66.7%
1 14
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 42
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 28
66.7%
1 14
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 42
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 28
66.7%
1 14
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 42
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 28
66.7%
1 14
33.3%

hospital_general_medical_11
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)7.1%
Missing986
Missing (%)98.6%
Memory size31.8 KiB
2023-12-09T23:29:06.173766image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters42
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row100
2nd row100
3rd row100
4th row100
5th row100
ValueCountFrequency (%)
100 14
100.0%
2023-12-09T23:29:06.476151image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 28
66.7%
1 14
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 42
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 28
66.7%
1 14
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 42
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 28
66.7%
1 14
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 42
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 28
66.7%
1 14
33.3%
Distinct12
Distinct (%)85.7%
Missing986
Missing (%)98.6%
Memory size31.8 KiB
2023-12-09T23:29:06.683305image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.5
Min length4

Characters and Unicode

Total characters91
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)71.4%

Sample

1st row3.09598
2nd row1.21138
3rd row0.46439
4th row3.09598
5th row2.96568
ValueCountFrequency (%)
0.46 2
14.3%
3.09598 2
14.3%
1.21138 1
7.1%
2.96568 1
7.1%
1.23079 1
7.1%
0.7436 1
7.1%
2.96868 1
7.1%
0.74685 1
7.1%
0.46571 1
7.1%
0.43118 1
7.1%
Other values (2) 2
14.3%
2023-12-09T23:29:07.023051image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 14
15.4%
4 11
12.1%
0 10
11.0%
6 10
11.0%
3 8
8.8%
9 8
8.8%
8 8
8.8%
1 8
8.8%
5 6
6.6%
2 4
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 77
84.6%
Other Punctuation 14
 
15.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 11
14.3%
0 10
13.0%
6 10
13.0%
3 8
10.4%
9 8
10.4%
8 8
10.4%
1 8
10.4%
5 6
7.8%
2 4
 
5.2%
7 4
 
5.2%
Other Punctuation
ValueCountFrequency (%)
. 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 91
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 14
15.4%
4 11
12.1%
0 10
11.0%
6 10
11.0%
3 8
8.8%
9 8
8.8%
8 8
8.8%
1 8
8.8%
5 6
6.6%
2 4
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 91
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 14
15.4%
4 11
12.1%
0 10
11.0%
6 10
11.0%
3 8
8.8%
9 8
8.8%
8 8
8.8%
1 8
8.8%
5 6
6.6%
2 4
 
4.4%
Distinct24
Distinct (%)100.0%
Missing976
Missing (%)97.6%
Memory size32.1 KiB
2023-12-09T23:29:07.285377image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length4.5
Mean length4.333333333
Min length3

Characters and Unicode

Total characters104
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)100.0%

Sample

1st row9007
2nd row29790
3rd row93725
4th row5403
5th row41644
ValueCountFrequency (%)
5403 1
 
4.2%
78798 1
 
4.2%
1285 1
 
4.2%
1850 1
 
4.2%
2000 1
 
4.2%
1740 1
 
4.2%
545 1
 
4.2%
44419 1
 
4.2%
900 1
 
4.2%
4127 1
 
4.2%
Other values (14) 14
58.3%
2023-12-09T23:29:07.662498image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 27
26.0%
4 16
15.4%
1 13
12.5%
5 10
 
9.6%
9 10
 
9.6%
2 10
 
9.6%
7 7
 
6.7%
3 5
 
4.8%
8 4
 
3.8%
6 2
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 104
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 27
26.0%
4 16
15.4%
1 13
12.5%
5 10
 
9.6%
9 10
 
9.6%
2 10
 
9.6%
7 7
 
6.7%
3 5
 
4.8%
8 4
 
3.8%
6 2
 
1.9%

Most occurring scripts

ValueCountFrequency (%)
Common 104
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 27
26.0%
4 16
15.4%
1 13
12.5%
5 10
 
9.6%
9 10
 
9.6%
2 10
 
9.6%
7 7
 
6.7%
3 5
 
4.8%
8 4
 
3.8%
6 2
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 104
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 27
26.0%
4 16
15.4%
1 13
12.5%
5 10
 
9.6%
9 10
 
9.6%
2 10
 
9.6%
7 7
 
6.7%
3 5
 
4.8%
8 4
 
3.8%
6 2
 
1.9%
Distinct2
Distinct (%)50.0%
Missing996
Missing (%)99.6%
Memory size31.5 KiB
2023-12-09T23:29:07.781165image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row1
3rd row0
4th row1
ValueCountFrequency (%)
1 2
50.0%
0 2
50.0%
2023-12-09T23:29:07.992688image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2
50.0%
0 2
50.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2
50.0%
0 2
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2
50.0%
0 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2
50.0%
0 2
50.0%
Distinct23
Distinct (%)95.8%
Missing976
Missing (%)97.6%
Memory size32.0 KiB
2023-12-09T23:29:08.180575image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.958333333
Min length1

Characters and Unicode

Total characters71
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)91.7%

Sample

1st row33
2nd row67.84
3rd row300
4th row11.89
5th row91.62
ValueCountFrequency (%)
2 2
 
8.3%
93 1
 
4.2%
97.72 1
 
4.2%
11.89 1
 
4.2%
80 1
 
4.2%
9.08 1
 
4.2%
300 1
 
4.2%
2.83 1
 
4.2%
350 1
 
4.2%
22 1
 
4.2%
Other values (13) 13
54.2%
2023-12-09T23:29:08.510969image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 11
15.5%
2 9
12.7%
3 9
12.7%
8 8
11.3%
9 7
9.9%
0 7
9.9%
4 6
8.5%
7 5
7.0%
1 4
 
5.6%
6 3
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60
84.5%
Other Punctuation 11
 
15.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 9
15.0%
3 9
15.0%
8 8
13.3%
9 7
11.7%
0 7
11.7%
4 6
10.0%
7 5
8.3%
1 4
6.7%
6 3
 
5.0%
5 2
 
3.3%
Other Punctuation
ValueCountFrequency (%)
. 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 71
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 11
15.5%
2 9
12.7%
3 9
12.7%
8 8
11.3%
9 7
9.9%
0 7
9.9%
4 6
8.5%
7 5
7.0%
1 4
 
5.6%
6 3
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 71
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 11
15.5%
2 9
12.7%
3 9
12.7%
8 8
11.3%
9 7
9.9%
0 7
9.9%
4 6
8.5%
7 5
7.0%
1 4
 
5.6%
6 3
 
4.2%
Distinct6
Distinct (%)25.0%
Missing976
Missing (%)97.6%
Memory size32.0 KiB
2023-12-09T23:29:08.644073image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.916666667
Min length2

Characters and Unicode

Total characters70
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)20.8%

Sample

1st row100
2nd row100
3rd row100
4th row100
5th row100
ValueCountFrequency (%)
100 19
79.2%
50 1
 
4.2%
10 1
 
4.2%
60 1
 
4.2%
80.85 1
 
4.2%
70 1
 
4.2%
2023-12-09T23:29:08.903929image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 43
61.4%
1 20
28.6%
5 2
 
2.9%
8 2
 
2.9%
6 1
 
1.4%
. 1
 
1.4%
7 1
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 69
98.6%
Other Punctuation 1
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 43
62.3%
1 20
29.0%
5 2
 
2.9%
8 2
 
2.9%
6 1
 
1.4%
7 1
 
1.4%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 70
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 43
61.4%
1 20
28.6%
5 2
 
2.9%
8 2
 
2.9%
6 1
 
1.4%
. 1
 
1.4%
7 1
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 70
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 43
61.4%
1 20
28.6%
5 2
 
2.9%
8 2
 
2.9%
6 1
 
1.4%
. 1
 
1.4%
7 1
 
1.4%
Distinct6
Distinct (%)25.0%
Missing976
Missing (%)97.6%
Memory size32.0 KiB
2023-12-09T23:29:09.037549image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.916666667
Min length2

Characters and Unicode

Total characters70
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)20.8%

Sample

1st row100
2nd row100
3rd row100
4th row100
5th row100
ValueCountFrequency (%)
100 19
79.2%
50 1
 
4.2%
10 1
 
4.2%
60 1
 
4.2%
80.85 1
 
4.2%
90 1
 
4.2%
2023-12-09T23:29:09.338484image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 43
61.4%
1 20
28.6%
5 2
 
2.9%
8 2
 
2.9%
6 1
 
1.4%
. 1
 
1.4%
9 1
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 69
98.6%
Other Punctuation 1
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 43
62.3%
1 20
29.0%
5 2
 
2.9%
8 2
 
2.9%
6 1
 
1.4%
9 1
 
1.4%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 70
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 43
61.4%
1 20
28.6%
5 2
 
2.9%
8 2
 
2.9%
6 1
 
1.4%
. 1
 
1.4%
9 1
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 70
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 43
61.4%
1 20
28.6%
5 2
 
2.9%
8 2
 
2.9%
6 1
 
1.4%
. 1
 
1.4%
9 1
 
1.4%

medical_office_weekly
Text

MISSING 

Distinct12
Distinct (%)50.0%
Missing976
Missing (%)97.6%
Memory size32.0 KiB
2023-12-09T23:29:09.502295image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.375
Min length2

Characters and Unicode

Total characters57
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)41.7%

Sample

1st row65
2nd row60
3rd row61.49
4th row65
5th row65
ValueCountFrequency (%)
65 12
50.0%
50 2
 
8.3%
80 1
 
4.2%
40 1
 
4.2%
60 1
 
4.2%
61.49 1
 
4.2%
70 1
 
4.2%
30 1
 
4.2%
57.38 1
 
4.2%
42 1
 
4.2%
Other values (2) 2
 
8.3%
2023-12-09T23:29:09.798474image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 16
28.1%
6 14
24.6%
0 7
12.3%
4 4
 
7.0%
. 3
 
5.3%
7 3
 
5.3%
3 3
 
5.3%
8 2
 
3.5%
1 2
 
3.5%
9 2
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 54
94.7%
Other Punctuation 3
 
5.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 16
29.6%
6 14
25.9%
0 7
13.0%
4 4
 
7.4%
7 3
 
5.6%
3 3
 
5.6%
8 2
 
3.7%
1 2
 
3.7%
9 2
 
3.7%
2 1
 
1.9%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 57
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 16
28.1%
6 14
24.6%
0 7
12.3%
4 4
 
7.0%
. 3
 
5.3%
7 3
 
5.3%
3 3
 
5.3%
8 2
 
3.5%
1 2
 
3.5%
9 2
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 57
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 16
28.1%
6 14
24.6%
0 7
12.3%
4 4
 
7.0%
. 3
 
5.3%
7 3
 
5.3%
3 3
 
5.3%
8 2
 
3.5%
1 2
 
3.5%
9 2
 
3.5%
Distinct3
Distinct (%)100.0%
Missing997
Missing (%)99.7%
Memory size31.5 KiB
2023-12-09T23:29:09.964417image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5
Min length4

Characters and Unicode

Total characters15
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st row102571
2nd row10400
3rd row1490
ValueCountFrequency (%)
10400 1
33.3%
1490 1
33.3%
102571 1
33.3%
2023-12-09T23:29:10.279710image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5
33.3%
1 4
26.7%
4 2
 
13.3%
9 1
 
6.7%
2 1
 
6.7%
5 1
 
6.7%
7 1
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5
33.3%
1 4
26.7%
4 2
 
13.3%
9 1
 
6.7%
2 1
 
6.7%
5 1
 
6.7%
7 1
 
6.7%

Most occurring scripts

ValueCountFrequency (%)
Common 15
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5
33.3%
1 4
26.7%
4 2
 
13.3%
9 1
 
6.7%
2 1
 
6.7%
5 1
 
6.7%
7 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5
33.3%
1 4
26.7%
4 2
 
13.3%
9 1
 
6.7%
2 1
 
6.7%
5 1
 
6.7%
7 1
 
6.7%
Distinct4
Distinct (%)100.0%
Missing996
Missing (%)99.6%
Memory size31.5 KiB
2023-12-09T23:29:10.464438image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length6
Mean length5.75
Min length5

Characters and Unicode

Total characters23
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st row105518
2nd row263550
3rd row160000
4th row17409
ValueCountFrequency (%)
105518 1
25.0%
17409 1
25.0%
160000 1
25.0%
263550 1
25.0%
2023-12-09T23:29:10.776472image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7
30.4%
1 4
17.4%
5 4
17.4%
6 2
 
8.7%
8 1
 
4.3%
7 1
 
4.3%
4 1
 
4.3%
9 1
 
4.3%
2 1
 
4.3%
3 1
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 23
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7
30.4%
1 4
17.4%
5 4
17.4%
6 2
 
8.7%
8 1
 
4.3%
7 1
 
4.3%
4 1
 
4.3%
9 1
 
4.3%
2 1
 
4.3%
3 1
 
4.3%

Most occurring scripts

ValueCountFrequency (%)
Common 23
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 7
30.4%
1 4
17.4%
5 4
17.4%
6 2
 
8.7%
8 1
 
4.3%
7 1
 
4.3%
4 1
 
4.3%
9 1
 
4.3%
2 1
 
4.3%
3 1
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7
30.4%
1 4
17.4%
5 4
17.4%
6 2
 
8.7%
8 1
 
4.3%
7 1
 
4.3%
4 1
 
4.3%
9 1
 
4.3%
2 1
 
4.3%
3 1
 
4.3%
Distinct19
Distinct (%)95.0%
Missing980
Missing (%)98.0%
Memory size32.0 KiB
2023-12-09T23:29:10.986016image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.05
Min length4

Characters and Unicode

Total characters101
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)90.0%

Sample

1st row94380
2nd row28581
3rd row71626
4th row181120
5th row39614
ValueCountFrequency (%)
39614 2
 
10.0%
58272 1
 
5.0%
77798 1
 
5.0%
181120 1
 
5.0%
18922 1
 
5.0%
60000 1
 
5.0%
75000 1
 
5.0%
58700 1
 
5.0%
41000 1
 
5.0%
61900 1
 
5.0%
Other values (9) 9
45.0%
2023-12-09T23:29:11.347095image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 23
22.8%
1 15
14.9%
7 11
10.9%
2 10
9.9%
8 10
9.9%
6 9
 
8.9%
5 8
 
7.9%
9 7
 
6.9%
3 4
 
4.0%
4 4
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 101
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 23
22.8%
1 15
14.9%
7 11
10.9%
2 10
9.9%
8 10
9.9%
6 9
 
8.9%
5 8
 
7.9%
9 7
 
6.9%
3 4
 
4.0%
4 4
 
4.0%

Most occurring scripts

ValueCountFrequency (%)
Common 101
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 23
22.8%
1 15
14.9%
7 11
10.9%
2 10
9.9%
8 10
9.9%
6 9
 
8.9%
5 8
 
7.9%
9 7
 
6.9%
3 4
 
4.0%
4 4
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 101
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 23
22.8%
1 15
14.9%
7 11
10.9%
2 10
9.9%
8 10
9.9%
6 9
 
8.9%
5 8
 
7.9%
9 7
 
6.9%
3 4
 
4.0%
4 4
 
4.0%
Distinct4
Distinct (%)100.0%
Missing996
Missing (%)99.6%
Memory size31.5 KiB
2023-12-09T23:29:11.538133image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length5.5
Mean length5.5
Min length5

Characters and Unicode

Total characters22
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st row685314
2nd row327993
3rd row91193
4th row54000
ValueCountFrequency (%)
685314 1
25.0%
54000 1
25.0%
327993 1
25.0%
91193 1
25.0%
2023-12-09T23:29:11.843284image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 4
18.2%
9 4
18.2%
1 3
13.6%
0 3
13.6%
5 2
9.1%
4 2
9.1%
6 1
 
4.5%
8 1
 
4.5%
2 1
 
4.5%
7 1
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 22
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 4
18.2%
9 4
18.2%
1 3
13.6%
0 3
13.6%
5 2
9.1%
4 2
9.1%
6 1
 
4.5%
8 1
 
4.5%
2 1
 
4.5%
7 1
 
4.5%

Most occurring scripts

ValueCountFrequency (%)
Common 22
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 4
18.2%
9 4
18.2%
1 3
13.6%
0 3
13.6%
5 2
9.1%
4 2
9.1%
6 1
 
4.5%
8 1
 
4.5%
2 1
 
4.5%
7 1
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 4
18.2%
9 4
18.2%
1 3
13.6%
0 3
13.6%
5 2
9.1%
4 2
9.1%
6 1
 
4.5%
8 1
 
4.5%
2 1
 
4.5%
7 1
 
4.5%

mailing_center_post_office
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing999
Missing (%)99.9%
Memory size31.4 KiB
2023-12-09T23:29:11.979612image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters4
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row2500
ValueCountFrequency (%)
2500 1
100.0%
2023-12-09T23:29:12.226392image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2
50.0%
2 1
25.0%
5 1
25.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2
50.0%
2 1
25.0%
5 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2
50.0%
2 1
25.0%
5 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2
50.0%
2 1
25.0%
5 1
25.0%
Distinct11
Distinct (%)52.4%
Missing979
Missing (%)97.9%
Memory size32.0 KiB
2023-12-09T23:29:12.410002image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length8
Median length5
Mean length5.523809524
Min length5

Characters and Unicode

Total characters116
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)19.0%

Sample

1st row80000
2nd row360000
3rd row80000
4th row360000
5th row38150
ValueCountFrequency (%)
65968 5
23.8%
80000 2
 
9.5%
360000 2
 
9.5%
75000 2
 
9.5%
103916.5 2
 
9.5%
143840 2
 
9.5%
40480 2
 
9.5%
38150 1
 
4.8%
69625 1
 
4.8%
73313 1
 
4.8%
2023-12-09T23:29:12.730711image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 31
26.7%
6 16
13.8%
8 12
 
10.3%
5 11
 
9.5%
3 10
 
8.6%
9 9
 
7.8%
4 9
 
7.8%
1 8
 
6.9%
7 6
 
5.2%
. 2
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 114
98.3%
Other Punctuation 2
 
1.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 31
27.2%
6 16
14.0%
8 12
 
10.5%
5 11
 
9.6%
3 10
 
8.8%
9 9
 
7.9%
4 9
 
7.9%
1 8
 
7.0%
7 6
 
5.3%
2 2
 
1.8%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 116
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 31
26.7%
6 16
13.8%
8 12
 
10.3%
5 11
 
9.5%
3 10
 
8.6%
9 9
 
7.8%
4 9
 
7.8%
1 8
 
6.9%
7 6
 
5.2%
. 2
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 116
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 31
26.7%
6 16
13.8%
8 12
 
10.3%
5 11
 
9.5%
3 10
 
8.6%
9 9
 
7.8%
4 9
 
7.8%
1 8
 
6.9%
7 6
 
5.2%
. 2
 
1.7%

movie_theater_gross_floor
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing999
Missing (%)99.9%
Memory size31.4 KiB
2023-12-09T23:29:12.878948image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters4
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row7000
ValueCountFrequency (%)
7000 1
100.0%
2023-12-09T23:29:13.126940image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3
75.0%
7 1
 
25.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3
75.0%
7 1
 
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3
75.0%
7 1
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3
75.0%
7 1
 
25.0%
Distinct408
Distinct (%)81.4%
Missing499
Missing (%)49.9%
Memory size46.2 KiB
2023-12-09T23:29:13.562609image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.291417166
Min length5

Characters and Unicode

Total characters2651
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique347 ?
Unique (%)69.3%

Sample

1st row61950
2nd row68240
3rd row127500
4th row319967
5th row28432
ValueCountFrequency (%)
57000 6
 
1.2%
280358 6
 
1.2%
50000 6
 
1.2%
60000 6
 
1.2%
35000 4
 
0.8%
150000 4
 
0.8%
72000 4
 
0.8%
54000 4
 
0.8%
63000 4
 
0.8%
48000 3
 
0.6%
Other values (398) 454
90.6%
2023-12-09T23:29:14.197413image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 692
26.1%
5 257
 
9.7%
1 246
 
9.3%
2 234
 
8.8%
6 229
 
8.6%
8 223
 
8.4%
4 222
 
8.4%
3 212
 
8.0%
7 194
 
7.3%
9 142
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2651
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 692
26.1%
5 257
 
9.7%
1 246
 
9.3%
2 234
 
8.8%
6 229
 
8.6%
8 223
 
8.4%
4 222
 
8.4%
3 212
 
8.0%
7 194
 
7.3%
9 142
 
5.4%

Most occurring scripts

ValueCountFrequency (%)
Common 2651
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 692
26.1%
5 257
 
9.7%
1 246
 
9.3%
2 234
 
8.8%
6 229
 
8.6%
8 223
 
8.4%
4 222
 
8.4%
3 212
 
8.0%
7 194
 
7.3%
9 142
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2651
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 692
26.1%
5 257
 
9.7%
1 246
 
9.3%
2 234
 
8.8%
6 229
 
8.6%
8 223
 
8.4%
4 222
 
8.4%
3 212
 
8.0%
7 194
 
7.3%
9 142
 
5.4%
Distinct2
Distinct (%)0.5%
Missing635
Missing (%)63.5%
Memory size41.4 KiB
2023-12-09T23:29:14.343489image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length8
Median length2
Mean length3.2
Min length2

Characters and Unicode

Total characters1168
Distinct characters9
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 292
66.7%
100 73
 
16.7%
yes 73
 
16.7%
2023-12-09T23:29:14.617942image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 292
25.0%
o 292
25.0%
0 146
12.5%
1 73
 
6.2%
% 73
 
6.2%
73
 
6.2%
Y 73
 
6.2%
e 73
 
6.2%
s 73
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 438
37.5%
Uppercase Letter 365
31.2%
Decimal Number 219
18.8%
Other Punctuation 73
 
6.2%
Space Separator 73
 
6.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 292
66.7%
e 73
 
16.7%
s 73
 
16.7%
Uppercase Letter
ValueCountFrequency (%)
N 292
80.0%
Y 73
 
20.0%
Decimal Number
ValueCountFrequency (%)
0 146
66.7%
1 73
33.3%
Other Punctuation
ValueCountFrequency (%)
% 73
100.0%
Space Separator
ValueCountFrequency (%)
73
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 803
68.8%
Common 365
31.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 292
36.4%
o 292
36.4%
Y 73
 
9.1%
e 73
 
9.1%
s 73
 
9.1%
Common
ValueCountFrequency (%)
0 146
40.0%
1 73
20.0%
% 73
20.0%
73
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1168
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 292
25.0%
o 292
25.0%
0 146
12.5%
1 73
 
6.2%
% 73
 
6.2%
73
 
6.2%
Y 73
 
6.2%
e 73
 
6.2%
s 73
 
6.2%
Distinct295
Distinct (%)59.1%
Missing501
Missing (%)50.1%
Memory size45.1 KiB
2023-12-09T23:29:15.114443image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length6
Mean length3.24248497
Min length1

Characters and Unicode

Total characters1618
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique194 ?
Unique (%)38.9%

Sample

1st row6
2nd row9553.76
3rd row185
4th row450
5th row42
ValueCountFrequency (%)
84 9
 
1.8%
72 7
 
1.4%
81 7
 
1.4%
80 7
 
1.4%
119 7
 
1.4%
66 6
 
1.2%
98 6
 
1.2%
48 6
 
1.2%
572 6
 
1.2%
59 5
 
1.0%
Other values (285) 433
86.8%
2023-12-09T23:29:15.772496image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 238
14.7%
6 165
10.2%
2 156
9.6%
8 151
9.3%
. 145
9.0%
0 142
8.8%
4 141
8.7%
5 131
8.1%
9 128
7.9%
7 120
7.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1473
91.0%
Other Punctuation 145
 
9.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 238
16.2%
6 165
11.2%
2 156
10.6%
8 151
10.3%
0 142
9.6%
4 141
9.6%
5 131
8.9%
9 128
8.7%
7 120
8.1%
3 101
6.9%
Other Punctuation
ValueCountFrequency (%)
. 145
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1618
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 238
14.7%
6 165
10.2%
2 156
9.6%
8 151
9.3%
. 145
9.0%
0 142
8.8%
4 141
8.7%
5 131
8.1%
9 128
7.9%
7 120
7.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1618
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 238
14.7%
6 165
10.2%
2 156
9.6%
8 151
9.3%
. 145
9.0%
0 142
8.8%
4 141
8.7%
5 131
8.1%
9 128
7.9%
7 120
7.4%
Distinct40
Distinct (%)11.7%
Missing657
Missing (%)65.7%
Memory size40.1 KiB
2023-12-09T23:29:15.975723image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length1
Mean length1.142857143
Min length1

Characters and Unicode

Total characters392
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)7.9%

Sample

1st row0
2nd row0
3rd row0
4th row360
5th row0
ValueCountFrequency (%)
0 265
77.3%
5 10
 
2.9%
1 6
 
1.7%
8 5
 
1.5%
6 5
 
1.5%
10 5
 
1.5%
20 4
 
1.2%
4 4
 
1.2%
7 3
 
0.9%
3 3
 
0.9%
Other values (30) 33
 
9.6%
2023-12-09T23:29:16.284458image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 278
70.9%
1 22
 
5.6%
5 19
 
4.8%
2 14
 
3.6%
8 13
 
3.3%
6 13
 
3.3%
4 12
 
3.1%
3 11
 
2.8%
9 6
 
1.5%
7 4
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 392
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 278
70.9%
1 22
 
5.6%
5 19
 
4.8%
2 14
 
3.6%
8 13
 
3.3%
6 13
 
3.3%
4 12
 
3.1%
3 11
 
2.8%
9 6
 
1.5%
7 4
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
Common 392
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 278
70.9%
1 22
 
5.6%
5 19
 
4.8%
2 14
 
3.6%
8 13
 
3.3%
6 13
 
3.3%
4 12
 
3.1%
3 11
 
2.8%
9 6
 
1.5%
7 4
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 392
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 278
70.9%
1 22
 
5.6%
5 19
 
4.8%
2 14
 
3.6%
8 13
 
3.3%
6 13
 
3.3%
4 12
 
3.1%
3 11
 
2.8%
9 6
 
1.5%
7 4
 
1.0%
Distinct30
Distinct (%)8.3%
Missing638
Missing (%)63.8%
Memory size40.6 KiB
2023-12-09T23:29:16.451994image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.17679558
Min length1

Characters and Unicode

Total characters426
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)1.9%

Sample

1st row1
2nd row0
3rd row2
4th row0
5th row0
ValueCountFrequency (%)
0 103
28.5%
4 42
11.6%
5 34
 
9.4%
6 33
 
9.1%
3 25
 
6.9%
8 22
 
6.1%
2 20
 
5.5%
10 12
 
3.3%
1 9
 
2.5%
12 7
 
1.9%
Other values (20) 55
15.2%
2023-12-09T23:29:16.749413image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 126
29.6%
1 58
13.6%
4 48
 
11.3%
5 43
 
10.1%
6 39
 
9.2%
2 37
 
8.7%
3 33
 
7.7%
8 28
 
6.6%
7 7
 
1.6%
9 7
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 426
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 126
29.6%
1 58
13.6%
4 48
 
11.3%
5 43
 
10.1%
6 39
 
9.2%
2 37
 
8.7%
3 33
 
7.7%
8 28
 
6.6%
7 7
 
1.6%
9 7
 
1.6%

Most occurring scripts

ValueCountFrequency (%)
Common 426
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 126
29.6%
1 58
13.6%
4 48
 
11.3%
5 43
 
10.1%
6 39
 
9.2%
2 37
 
8.7%
3 33
 
7.7%
8 28
 
6.6%
7 7
 
1.6%
9 7
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 426
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 126
29.6%
1 58
13.6%
4 48
 
11.3%
5 43
 
10.1%
6 39
 
9.2%
2 37
 
8.7%
3 33
 
7.7%
8 28
 
6.6%
7 7
 
1.6%
9 7
 
1.6%
Distinct220
Distinct (%)44.0%
Missing500
Missing (%)50.0%
Memory size44.9 KiB
2023-12-09T23:29:17.996873image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length2
Mean length2.652
Min length1

Characters and Unicode

Total characters1326
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique129 ?
Unique (%)25.8%

Sample

1st row69
2nd row56
3rd row139
4th row375
5th row36
ValueCountFrequency (%)
36 15
 
3.0%
37 15
 
3.0%
66 12
 
2.4%
54 10
 
2.0%
73 10
 
2.0%
81 8
 
1.6%
42 8
 
1.6%
72 8
 
1.6%
48 7
 
1.4%
59 7
 
1.4%
Other values (210) 400
80.0%
2023-12-09T23:29:18.613473image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 173
13.0%
3 154
11.6%
1 150
11.3%
2 133
10.0%
7 125
9.4%
4 121
9.1%
5 116
8.7%
8 113
8.5%
9 96
7.2%
0 74
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1255
94.6%
Other Punctuation 71
 
5.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 173
13.8%
3 154
12.3%
1 150
12.0%
2 133
10.6%
7 125
10.0%
4 121
9.6%
5 116
9.2%
8 113
9.0%
9 96
7.6%
0 74
5.9%
Other Punctuation
ValueCountFrequency (%)
. 71
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1326
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 173
13.0%
3 154
11.6%
1 150
11.3%
2 133
10.0%
7 125
9.4%
4 121
9.1%
5 116
8.7%
8 113
8.5%
9 96
7.2%
0 74
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1326
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 173
13.0%
3 154
11.6%
1 150
11.3%
2 133
10.0%
7 125
9.4%
4 121
9.1%
5 116
8.7%
8 113
8.5%
9 96
7.2%
0 74
5.6%
Distinct10
Distinct (%)2.3%
Missing573
Missing (%)57.3%
Memory size42.6 KiB
2023-12-09T23:29:18.787432image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2
Min length1

Characters and Unicode

Total characters854
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row100
2nd row0
3rd row0
4th row100
5th row100
ValueCountFrequency (%)
0 135
31.6%
100 135
31.6%
90 71
16.6%
60 43
 
10.1%
10 13
 
3.0%
80 10
 
2.3%
50 9
 
2.1%
70 8
 
1.9%
30 2
 
0.5%
20 1
 
0.2%
2023-12-09T23:29:19.081980image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 562
65.8%
1 148
 
17.3%
9 71
 
8.3%
6 43
 
5.0%
8 10
 
1.2%
5 9
 
1.1%
7 8
 
0.9%
3 2
 
0.2%
2 1
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 854
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 562
65.8%
1 148
 
17.3%
9 71
 
8.3%
6 43
 
5.0%
8 10
 
1.2%
5 9
 
1.1%
7 8
 
0.9%
3 2
 
0.2%
2 1
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 854
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 562
65.8%
1 148
 
17.3%
9 71
 
8.3%
6 43
 
5.0%
8 10
 
1.2%
5 9
 
1.1%
7 8
 
0.9%
3 2
 
0.2%
2 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 854
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 562
65.8%
1 148
 
17.3%
9 71
 
8.3%
6 43
 
5.0%
8 10
 
1.2%
5 9
 
1.1%
7 8
 
0.9%
3 2
 
0.2%
2 1
 
0.1%
Distinct7
Distinct (%)1.6%
Missing560
Missing (%)56.0%
Memory size43.3 KiB
2023-12-09T23:29:19.216304image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.720454545
Min length1

Characters and Unicode

Total characters1197
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row100
2nd row100
3rd row100
4th row100
5th row100
ValueCountFrequency (%)
100 328
74.5%
80 41
 
9.3%
90 37
 
8.4%
10 11
 
2.5%
0 11
 
2.5%
50 8
 
1.8%
70 4
 
0.9%
2023-12-09T23:29:19.481029image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 768
64.2%
1 339
28.3%
8 41
 
3.4%
9 37
 
3.1%
5 8
 
0.7%
7 4
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1197
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 768
64.2%
1 339
28.3%
8 41
 
3.4%
9 37
 
3.1%
5 8
 
0.7%
7 4
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Common 1197
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 768
64.2%
1 339
28.3%
8 41
 
3.4%
9 37
 
3.1%
5 8
 
0.7%
7 4
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1197
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 768
64.2%
1 339
28.3%
8 41
 
3.4%
9 37
 
3.1%
5 8
 
0.7%
7 4
 
0.3%
Distinct3
Distinct (%)0.9%
Missing658
Missing (%)65.8%
Memory size50.0 KiB
2023-12-09T23:29:19.674050image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length35
Median length31
Mean length30.75438596
Min length23

Characters and Unicode

Total characters10518
Distinct characters25
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo specific resident population
2nd rowNo specific resident population
3rd rowNo specific resident population
4th rowNo specific resident population
5th rowNo specific resident population
ValueCountFrequency (%)
no 327
24.2%
specific 327
24.2%
resident 327
24.2%
population 327
24.2%
dedicated 15
 
1.1%
other 12
 
0.9%
housing 12
 
0.9%
senior/independent 3
 
0.2%
living 3
 
0.2%
2023-12-09T23:29:19.989203image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 1344
12.8%
e 1035
9.8%
1011
9.6%
o 996
9.5%
p 984
9.4%
t 684
 
6.5%
n 681
 
6.5%
c 669
 
6.4%
s 666
 
6.3%
d 375
 
3.6%
Other values (15) 2073
19.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 9153
87.0%
Space Separator 1011
 
9.6%
Uppercase Letter 351
 
3.3%
Other Punctuation 3
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 1344
14.7%
e 1035
11.3%
o 996
10.9%
p 984
10.8%
t 684
7.5%
n 681
7.4%
c 669
7.3%
s 666
7.3%
d 375
 
4.1%
a 342
 
3.7%
Other values (7) 1377
15.0%
Uppercase Letter
ValueCountFrequency (%)
N 327
93.2%
O 12
 
3.4%
D 3
 
0.9%
S 3
 
0.9%
I 3
 
0.9%
L 3
 
0.9%
Space Separator
ValueCountFrequency (%)
1011
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 9504
90.4%
Common 1014
 
9.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 1344
14.1%
e 1035
10.9%
o 996
10.5%
p 984
10.4%
t 684
 
7.2%
n 681
 
7.2%
c 669
 
7.0%
s 666
 
7.0%
d 375
 
3.9%
a 342
 
3.6%
Other values (13) 1728
18.2%
Common
ValueCountFrequency (%)
1011
99.7%
/ 3
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10518
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 1344
12.8%
e 1035
9.8%
1011
9.6%
o 996
9.5%
p 984
9.4%
t 684
 
6.5%
n 681
 
6.5%
c 669
 
6.4%
s 666
 
6.3%
d 375
 
3.6%
Other values (15) 2073
19.7%
Distinct309
Distinct (%)61.9%
Missing501
Missing (%)50.1%
Memory size46.3 KiB
2023-12-09T23:29:20.370346image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length8
Median length7
Mean length5.559118236
Min length1

Characters and Unicode

Total characters2774
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique274 ?
Unique (%)54.9%

Sample

1st row0.09685
2nd row140.0023
3rd row1.45098
4th row1.4064
5th row1.47721
ValueCountFrequency (%)
1.4 145
29.1%
1.6 6
 
1.2%
2.04025 6
 
1.2%
1.19 3
 
0.6%
0 3
 
0.6%
1.38596 3
 
0.6%
1.25 3
 
0.6%
1.48993 2
 
0.4%
1.88144 2
 
0.4%
1.23611 2
 
0.4%
Other values (299) 324
64.9%
2023-12-09T23:29:20.894405image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 562
20.3%
. 495
17.8%
4 335
12.1%
0 204
 
7.4%
2 196
 
7.1%
9 177
 
6.4%
3 176
 
6.3%
8 169
 
6.1%
5 160
 
5.8%
6 158
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2279
82.2%
Other Punctuation 495
 
17.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 562
24.7%
4 335
14.7%
0 204
 
9.0%
2 196
 
8.6%
9 177
 
7.8%
3 176
 
7.7%
8 169
 
7.4%
5 160
 
7.0%
6 158
 
6.9%
7 142
 
6.2%
Other Punctuation
ValueCountFrequency (%)
. 495
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2774
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 562
20.3%
. 495
17.8%
4 335
12.1%
0 204
 
7.4%
2 196
 
7.1%
9 177
 
6.4%
3 176
 
6.3%
8 169
 
6.1%
5 160
 
5.8%
6 158
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2774
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 562
20.3%
. 495
17.8%
4 335
12.1%
0 204
 
7.4%
2 196
 
7.1%
9 177
 
6.4%
3 176
 
6.3%
8 169
 
6.1%
5 160
 
5.8%
6 158
 
5.7%
Distinct364
Distinct (%)72.8%
Missing500
Missing (%)50.0%
Memory size46.6 KiB
2023-12-09T23:29:21.267599image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.106
Min length1

Characters and Unicode

Total characters3053
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique315 ?
Unique (%)63.0%

Sample

1st row1.1138
2nd row0.82063
3rd row1.0902
4th row1.172
5th row1.26618
ValueCountFrequency (%)
1.2 75
 
15.0%
1 8
 
1.6%
1.02012 6
 
1.2%
1.44 3
 
0.6%
0.98246 3
 
0.6%
0.81 3
 
0.6%
1.14286 3
 
0.6%
0.97593 2
 
0.4%
1.03125 2
 
0.4%
0.97333 2
 
0.4%
Other values (354) 393
78.6%
2023-12-09T23:29:21.764878image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 498
16.3%
. 491
16.1%
0 427
14.0%
2 286
9.4%
8 246
8.1%
9 243
8.0%
6 191
 
6.3%
3 176
 
5.8%
4 173
 
5.7%
5 170
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2562
83.9%
Other Punctuation 491
 
16.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 498
19.4%
0 427
16.7%
2 286
11.2%
8 246
9.6%
9 243
9.5%
6 191
 
7.5%
3 176
 
6.9%
4 173
 
6.8%
5 170
 
6.6%
7 152
 
5.9%
Other Punctuation
ValueCountFrequency (%)
. 491
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3053
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 498
16.3%
. 491
16.1%
0 427
14.0%
2 286
9.4%
8 246
8.1%
9 243
8.0%
6 191
 
6.3%
3 176
 
5.8%
4 173
 
5.7%
5 170
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3053
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 498
16.3%
. 491
16.1%
0 427
14.0%
2 286
9.4%
8 246
8.1%
9 243
8.0%
6 191
 
6.3%
3 176
 
5.8%
4 173
 
5.7%
5 170
 
5.6%
Distinct65
Distinct (%)13.0%
Missing500
Missing (%)50.0%
Memory size44.2 KiB
2023-12-09T23:29:22.014500image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length1
Mean length1.258
Min length1

Characters and Unicode

Total characters629
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique53 ?
Unique (%)10.6%

Sample

1st row0
2nd row0
3rd row0
4th row375
5th row0
ValueCountFrequency (%)
0 417
83.4%
286 6
 
1.2%
37 5
 
1.0%
5 3
 
0.6%
99 2
 
0.4%
129 2
 
0.4%
1169 2
 
0.4%
28 2
 
0.4%
12 2
 
0.4%
117 2
 
0.4%
Other values (55) 57
 
11.4%
2023-12-09T23:29:22.382427image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 430
68.4%
2 35
 
5.6%
1 31
 
4.9%
3 26
 
4.1%
8 22
 
3.5%
6 22
 
3.5%
7 21
 
3.3%
9 18
 
2.9%
5 13
 
2.1%
4 11
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 629
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 430
68.4%
2 35
 
5.6%
1 31
 
4.9%
3 26
 
4.1%
8 22
 
3.5%
6 22
 
3.5%
7 21
 
3.3%
9 18
 
2.9%
5 13
 
2.1%
4 11
 
1.7%

Most occurring scripts

ValueCountFrequency (%)
Common 629
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 430
68.4%
2 35
 
5.6%
1 31
 
4.9%
3 26
 
4.1%
8 22
 
3.5%
6 22
 
3.5%
7 21
 
3.3%
9 18
 
2.9%
5 13
 
2.1%
4 11
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 629
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 430
68.4%
2 35
 
5.6%
1 31
 
4.9%
3 26
 
4.1%
8 22
 
3.5%
6 22
 
3.5%
7 21
 
3.3%
9 18
 
2.9%
5 13
 
2.1%
4 11
 
1.7%
Distinct73
Distinct (%)14.6%
Missing500
Missing (%)50.0%
Memory size44.5 KiB
2023-12-09T23:29:22.664069image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length1
Mean length1.954
Min length1

Characters and Unicode

Total characters977
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique66 ?
Unique (%)13.2%

Sample

1st row0
2nd row0
3rd row0
4th row1.172
5th row0
ValueCountFrequency (%)
0 417
83.4%
1.02012 6
 
1.2%
0.37 3
 
0.6%
0.97333 2
 
0.4%
0.72166 2
 
0.4%
1.09522 2
 
0.4%
0.91881 2
 
0.4%
0.92431 1
 
0.2%
1.27012 1
 
0.2%
1.13105 1
 
0.2%
Other values (63) 63
 
12.6%
2023-12-09T23:29:23.073052image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 518
53.0%
. 83
 
8.5%
1 68
 
7.0%
2 56
 
5.7%
3 40
 
4.1%
9 39
 
4.0%
7 37
 
3.8%
5 36
 
3.7%
8 35
 
3.6%
4 35
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 894
91.5%
Other Punctuation 83
 
8.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 518
57.9%
1 68
 
7.6%
2 56
 
6.3%
3 40
 
4.5%
9 39
 
4.4%
7 37
 
4.1%
5 36
 
4.0%
8 35
 
3.9%
4 35
 
3.9%
6 30
 
3.4%
Other Punctuation
ValueCountFrequency (%)
. 83
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 977
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 518
53.0%
. 83
 
8.5%
1 68
 
7.0%
2 56
 
5.7%
3 40
 
4.1%
9 39
 
4.0%
7 37
 
3.8%
5 36
 
3.7%
8 35
 
3.6%
4 35
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 977
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 518
53.0%
. 83
 
8.5%
1 68
 
7.0%
2 56
 
5.7%
3 40
 
4.1%
9 39
 
4.0%
7 37
 
3.8%
5 36
 
3.7%
8 35
 
3.6%
4 35
 
3.6%
Distinct120
Distinct (%)24.0%
Missing501
Missing (%)50.1%
Memory size44.4 KiB
2023-12-09T23:29:23.408388image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length3
Mean length1.657314629
Min length1

Characters and Unicode

Total characters827
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique54 ?
Unique (%)10.8%

Sample

1st row0
2nd row56
3rd row139
4th row0
5th row0
ValueCountFrequency (%)
0 195
39.1%
16 13
 
2.6%
12 10
 
2.0%
66 8
 
1.6%
18 8
 
1.6%
50 7
 
1.4%
73 6
 
1.2%
7 6
 
1.2%
29 6
 
1.2%
40 6
 
1.2%
Other values (110) 234
46.9%
2023-12-09T23:29:23.859707image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 240
29.0%
1 107
12.9%
6 81
 
9.8%
2 72
 
8.7%
3 64
 
7.7%
7 60
 
7.3%
5 57
 
6.9%
4 54
 
6.5%
8 46
 
5.6%
9 45
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 826
99.9%
Other Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 240
29.1%
1 107
13.0%
6 81
 
9.8%
2 72
 
8.7%
3 64
 
7.7%
7 60
 
7.3%
5 57
 
6.9%
4 54
 
6.5%
8 46
 
5.6%
9 45
 
5.4%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 827
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 240
29.0%
1 107
12.9%
6 81
 
9.8%
2 72
 
8.7%
3 64
 
7.7%
7 60
 
7.3%
5 57
 
6.9%
4 54
 
6.5%
8 46
 
5.6%
9 45
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 827
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 240
29.0%
1 107
12.9%
6 81
 
9.8%
2 72
 
8.7%
3 64
 
7.7%
7 60
 
7.3%
5 57
 
6.9%
4 54
 
6.5%
8 46
 
5.6%
9 45
 
5.4%
Distinct266
Distinct (%)53.3%
Missing501
Missing (%)50.1%
Memory size45.7 KiB
2023-12-09T23:29:24.246131image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length7
Mean length4.496993988
Min length1

Characters and Unicode

Total characters2244
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique231 ?
Unique (%)46.3%

Sample

1st row0
2nd row0.82063
3rd row1.0902
4th row0
5th row0
ValueCountFrequency (%)
0 195
39.1%
1.14286 3
 
0.6%
0.2807 3
 
0.6%
0.29 3
 
0.6%
0.33333 3
 
0.6%
1.44 3
 
0.6%
0.28569 2
 
0.4%
1.12285 2
 
0.4%
0.98039 2
 
0.4%
0.80645 2
 
0.4%
Other values (256) 281
56.3%
2023-12-09T23:29:24.791030image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 540
24.1%
. 302
13.5%
1 231
10.3%
3 170
 
7.6%
2 162
 
7.2%
4 159
 
7.1%
8 152
 
6.8%
9 151
 
6.7%
5 136
 
6.1%
6 130
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1942
86.5%
Other Punctuation 302
 
13.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 540
27.8%
1 231
11.9%
3 170
 
8.8%
2 162
 
8.3%
4 159
 
8.2%
8 152
 
7.8%
9 151
 
7.8%
5 136
 
7.0%
6 130
 
6.7%
7 111
 
5.7%
Other Punctuation
ValueCountFrequency (%)
. 302
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2244
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 540
24.1%
. 302
13.5%
1 231
10.3%
3 170
 
7.6%
2 162
 
7.2%
4 159
 
7.1%
8 152
 
6.8%
9 151
 
6.7%
5 136
 
6.1%
6 130
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2244
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 540
24.1%
. 302
13.5%
1 231
10.3%
3 170
 
7.6%
2 162
 
7.2%
4 159
 
7.1%
8 152
 
6.8%
9 151
 
6.7%
5 136
 
6.1%
6 130
 
5.8%
Distinct46
Distinct (%)83.6%
Missing945
Missing (%)94.5%
Memory size33.0 KiB
2023-12-09T23:29:25.060999image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length8
Median length7
Mean length5.872727273
Min length1

Characters and Unicode

Total characters323
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)76.4%

Sample

1st row0.20207
2nd row0.65488
3rd row0
4th row0.27058
5th row0
ValueCountFrequency (%)
0 7
 
12.7%
1.71429 2
 
3.6%
0.27058 2
 
3.6%
1.99734 2
 
3.6%
0.26236 1
 
1.8%
2.57732 1
 
1.8%
0.1 1
 
1.8%
0.39695 1
 
1.8%
0.30612 1
 
1.8%
0.21875 1
 
1.8%
Other values (36) 36
65.5%
2023-12-09T23:29:25.460575image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 50
15.5%
. 47
14.6%
1 32
9.9%
3 29
9.0%
5 28
8.7%
6 27
8.4%
2 25
7.7%
7 25
7.7%
4 22
6.8%
9 21
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 276
85.4%
Other Punctuation 47
 
14.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 50
18.1%
1 32
11.6%
3 29
10.5%
5 28
10.1%
6 27
9.8%
2 25
9.1%
7 25
9.1%
4 22
8.0%
9 21
7.6%
8 17
 
6.2%
Other Punctuation
ValueCountFrequency (%)
. 47
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 323
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 50
15.5%
. 47
14.6%
1 32
9.9%
3 29
9.0%
5 28
8.7%
6 27
8.4%
2 25
7.7%
7 25
7.7%
4 22
6.8%
9 21
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 323
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 50
15.5%
. 47
14.6%
1 32
9.9%
3 29
9.0%
5 28
8.7%
6 27
8.4%
2 25
7.7%
7 25
7.7%
4 22
6.8%
9 21
6.5%
Distinct209
Distinct (%)90.1%
Missing768
Missing (%)76.8%
Memory size38.3 KiB
2023-12-09T23:29:25.895713image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length8
Median length6
Mean length5.637931034
Min length3

Characters and Unicode

Total characters1308
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique187 ?
Unique (%)80.6%

Sample

1st row164754
2nd row9134
3rd row69851
4th row99117
5th row871546
ValueCountFrequency (%)
1111437 3
 
1.3%
60000 2
 
0.9%
32500 2
 
0.9%
2751552 2
 
0.9%
809400 2
 
0.9%
58862 2
 
0.9%
39655 2
 
0.9%
48050 2
 
0.9%
3510 2
 
0.9%
476000 2
 
0.9%
Other values (199) 211
90.9%
2023-12-09T23:29:26.470595image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 267
20.4%
1 173
13.2%
5 136
10.4%
2 128
9.8%
4 114
8.7%
3 106
 
8.1%
6 106
 
8.1%
8 96
 
7.3%
7 94
 
7.2%
9 85
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1305
99.8%
Other Punctuation 3
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 267
20.5%
1 173
13.3%
5 136
10.4%
2 128
9.8%
4 114
8.7%
3 106
 
8.1%
6 106
 
8.1%
8 96
 
7.4%
7 94
 
7.2%
9 85
 
6.5%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1308
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 267
20.4%
1 173
13.2%
5 136
10.4%
2 128
9.8%
4 114
8.7%
3 106
 
8.1%
6 106
 
8.1%
8 96
 
7.3%
7 94
 
7.2%
9 85
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1308
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 267
20.4%
1 173
13.2%
5 136
10.4%
2 128
9.8%
4 114
8.7%
3 106
 
8.1%
6 106
 
8.1%
8 96
 
7.3%
7 94
 
7.2%
9 85
 
6.5%
Distinct184
Distinct (%)79.3%
Missing768
Missing (%)76.8%
Memory size37.9 KiB
2023-12-09T23:29:26.981490image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length6
Mean length3.698275862
Min length1

Characters and Unicode

Total characters858
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique158 ?
Unique (%)68.1%

Sample

1st row515.67
2nd row18.27
3rd row56
4th row300
5th row3500
ValueCountFrequency (%)
300 8
 
3.4%
2 8
 
3.4%
3500 5
 
2.2%
100 4
 
1.7%
50 3
 
1.3%
990 3
 
1.3%
150 3
 
1.3%
800 3
 
1.3%
600 3
 
1.3%
220 2
 
0.9%
Other values (174) 190
81.9%
2023-12-09T23:29:27.656743image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 158
18.4%
1 110
12.8%
3 93
10.8%
2 88
10.3%
5 80
9.3%
4 61
 
7.1%
6 59
 
6.9%
. 57
 
6.6%
8 53
 
6.2%
7 51
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 801
93.4%
Other Punctuation 57
 
6.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 158
19.7%
1 110
13.7%
3 93
11.6%
2 88
11.0%
5 80
10.0%
4 61
 
7.6%
6 59
 
7.4%
8 53
 
6.6%
7 51
 
6.4%
9 48
 
6.0%
Other Punctuation
ValueCountFrequency (%)
. 57
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 858
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 158
18.4%
1 110
12.8%
3 93
10.8%
2 88
10.3%
5 80
9.3%
4 61
 
7.1%
6 59
 
6.9%
. 57
 
6.6%
8 53
 
6.2%
7 51
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 858
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 158
18.4%
1 110
12.8%
3 93
10.8%
2 88
10.3%
5 80
9.3%
4 61
 
7.1%
6 59
 
6.9%
. 57
 
6.6%
8 53
 
6.2%
7 51
 
5.9%
Distinct189
Distinct (%)81.5%
Missing768
Missing (%)76.8%
Memory size37.9 KiB
2023-12-09T23:29:28.229984image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length6
Mean length3.801724138
Min length1

Characters and Unicode

Total characters882
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique159 ?
Unique (%)68.5%

Sample

1st row429.91
2nd row21.01
3rd row80
4th row280
5th row3431
ValueCountFrequency (%)
50 5
 
2.2%
300 5
 
2.2%
1.5 4
 
1.7%
6 4
 
1.7%
100 3
 
1.3%
150 3
 
1.3%
3500 3
 
1.3%
500 2
 
0.9%
2.3 2
 
0.9%
990 2
 
0.9%
Other values (179) 199
85.8%
2023-12-09T23:29:28.872958image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 135
15.3%
5 111
12.6%
1 109
12.4%
2 90
10.2%
3 88
10.0%
6 67
7.6%
. 66
7.5%
4 65
7.4%
7 58
6.6%
9 48
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 816
92.5%
Other Punctuation 66
 
7.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 135
16.5%
5 111
13.6%
1 109
13.4%
2 90
11.0%
3 88
10.8%
6 67
8.2%
4 65
8.0%
7 58
7.1%
9 48
 
5.9%
8 45
 
5.5%
Other Punctuation
ValueCountFrequency (%)
. 66
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 882
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 135
15.3%
5 111
12.6%
1 109
12.4%
2 90
10.2%
3 88
10.0%
6 67
7.6%
. 66
7.5%
4 65
7.4%
7 58
6.6%
9 48
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 882
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 135
15.3%
5 111
12.6%
1 109
12.4%
2 90
10.2%
3 88
10.0%
6 67
7.6%
. 66
7.5%
4 65
7.4%
7 58
6.6%
9 48
 
5.4%
Distinct11
Distinct (%)4.7%
Missing768
Missing (%)76.8%
Memory size37.7 KiB
2023-12-09T23:29:29.027371image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.051724138
Min length2

Characters and Unicode

Total characters708
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)3.9%

Sample

1st row100
2nd row100
3rd row100
4th row100
5th row100
ValueCountFrequency (%)
100 218
94.0%
25 5
 
2.2%
62.95 1
 
0.4%
75.1 1
 
0.4%
99.86 1
 
0.4%
96.66 1
 
0.4%
89.65 1
 
0.4%
95.11 1
 
0.4%
89.29 1
 
0.4%
83.75 1
 
0.4%
2023-12-09T23:29:29.291908image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 436
61.6%
1 221
31.2%
5 10
 
1.4%
. 9
 
1.3%
2 8
 
1.1%
9 8
 
1.1%
6 6
 
0.8%
8 5
 
0.7%
7 2
 
0.3%
4 2
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 699
98.7%
Other Punctuation 9
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 436
62.4%
1 221
31.6%
5 10
 
1.4%
2 8
 
1.1%
9 8
 
1.1%
6 6
 
0.9%
8 5
 
0.7%
7 2
 
0.3%
4 2
 
0.3%
3 1
 
0.1%
Other Punctuation
ValueCountFrequency (%)
. 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 708
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 436
61.6%
1 221
31.2%
5 10
 
1.4%
. 9
 
1.3%
2 8
 
1.1%
9 8
 
1.1%
6 6
 
0.8%
8 5
 
0.7%
7 2
 
0.3%
4 2
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 708
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 436
61.6%
1 221
31.2%
5 10
 
1.4%
. 9
 
1.3%
2 8
 
1.1%
9 8
 
1.1%
6 6
 
0.8%
8 5
 
0.7%
7 2
 
0.3%
4 2
 
0.3%
Distinct11
Distinct (%)4.7%
Missing768
Missing (%)76.8%
Memory size37.7 KiB
2023-12-09T23:29:29.440043image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.051724138
Min length1

Characters and Unicode

Total characters708
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)3.9%

Sample

1st row100
2nd row100
3rd row100
4th row100
5th row100
ValueCountFrequency (%)
100 221
95.3%
33 2
 
0.9%
97.01 1
 
0.4%
99.86 1
 
0.4%
90.75 1
 
0.4%
85.48 1
 
0.4%
95.11 1
 
0.4%
0 1
 
0.4%
84.31 1
 
0.4%
65.22 1
 
0.4%
2023-12-09T23:29:29.716901image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 446
63.0%
1 225
31.8%
. 8
 
1.1%
3 6
 
0.8%
9 6
 
0.8%
8 4
 
0.6%
5 4
 
0.6%
4 3
 
0.4%
7 2
 
0.3%
6 2
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 700
98.9%
Other Punctuation 8
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 446
63.7%
1 225
32.1%
3 6
 
0.9%
9 6
 
0.9%
8 4
 
0.6%
5 4
 
0.6%
4 3
 
0.4%
7 2
 
0.3%
6 2
 
0.3%
2 2
 
0.3%
Other Punctuation
ValueCountFrequency (%)
. 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 708
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 446
63.0%
1 225
31.8%
. 8
 
1.1%
3 6
 
0.8%
9 6
 
0.8%
8 4
 
0.6%
5 4
 
0.6%
4 3
 
0.4%
7 2
 
0.3%
6 2
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 708
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 446
63.0%
1 225
31.8%
. 8
 
1.1%
3 6
 
0.8%
9 6
 
0.8%
8 4
 
0.6%
5 4
 
0.6%
4 3
 
0.4%
7 2
 
0.3%
6 2
 
0.3%
Distinct100
Distinct (%)43.1%
Missing768
Missing (%)76.8%
Memory size37.7 KiB
2023-12-09T23:29:30.047401image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length2
Mean length3.038793103
Min length1

Characters and Unicode

Total characters705
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique82 ?
Unique (%)35.3%

Sample

1st row48
2nd row65
3rd row40
4th row49
5th row40
ValueCountFrequency (%)
65 42
18.1%
50 34
 
14.7%
60 14
 
6.0%
40 13
 
5.6%
55 8
 
3.4%
70 8
 
3.4%
45 7
 
3.0%
49 3
 
1.3%
44.5 3
 
1.3%
44.32 2
 
0.9%
Other values (90) 98
42.2%
2023-12-09T23:29:30.526431image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 154
21.8%
6 107
15.2%
0 85
12.1%
4 85
12.1%
. 82
11.6%
7 41
 
5.8%
1 34
 
4.8%
8 34
 
4.8%
9 31
 
4.4%
3 27
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 623
88.4%
Other Punctuation 82
 
11.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 154
24.7%
6 107
17.2%
0 85
13.6%
4 85
13.6%
7 41
 
6.6%
1 34
 
5.5%
8 34
 
5.5%
9 31
 
5.0%
3 27
 
4.3%
2 25
 
4.0%
Other Punctuation
ValueCountFrequency (%)
. 82
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 705
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 154
21.8%
6 107
15.2%
0 85
12.1%
4 85
12.1%
. 82
11.6%
7 41
 
5.8%
1 34
 
4.8%
8 34
 
4.8%
9 31
 
4.4%
3 27
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 705
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 154
21.8%
6 107
15.2%
0 85
12.1%
4 85
12.1%
. 82
11.6%
7 41
 
5.8%
1 34
 
4.8%
8 34
 
4.8%
9 31
 
4.4%
3 27
 
3.8%
Distinct189
Distinct (%)81.5%
Missing768
Missing (%)76.8%
Memory size38.5 KiB
2023-12-09T23:29:30.912109image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length8
Median length7
Mean length6.331896552
Min length1

Characters and Unicode

Total characters1469
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique170 ?
Unique (%)73.3%

Sample

1st row2.60939
2nd row2.3
3rd row1.1453
4th row2.82494
5th row3.93668
ValueCountFrequency (%)
2.3 25
 
10.8%
3.14908 3
 
1.3%
3.94737 2
 
0.9%
2.5 2
 
0.9%
3.02343 2
 
0.9%
0.04615 2
 
0.9%
1.69889 2
 
0.9%
2.33883 2
 
0.9%
2.56723 2
 
0.9%
4.8409 2
 
0.9%
Other values (179) 188
81.0%
2023-12-09T23:29:31.429627image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 230
15.7%
2 203
13.8%
3 177
12.0%
1 124
8.4%
4 123
8.4%
6 117
8.0%
7 112
7.6%
9 103
7.0%
0 103
7.0%
5 95
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1239
84.3%
Other Punctuation 230
 
15.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 203
16.4%
3 177
14.3%
1 124
10.0%
4 123
9.9%
6 117
9.4%
7 112
9.0%
9 103
8.3%
0 103
8.3%
5 95
7.7%
8 82
6.6%
Other Punctuation
ValueCountFrequency (%)
. 230
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1469
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 230
15.7%
2 203
13.8%
3 177
12.0%
1 124
8.4%
4 123
8.4%
6 117
8.0%
7 112
7.6%
9 103
7.0%
0 103
7.0%
5 95
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1469
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 230
15.7%
2 203
13.8%
3 177
12.0%
1 124
8.4%
4 123
8.4%
6 117
8.0%
7 112
7.6%
9 103
7.0%
0 103
7.0%
5 95
6.5%
Distinct4
Distinct (%)80.0%
Missing995
Missing (%)99.5%
Memory size31.5 KiB
2023-12-09T23:29:31.618718image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.4
Min length5

Characters and Unicode

Total characters27
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)60.0%

Sample

1st row220000
2nd row197509
3rd row85000
4th row85000
5th row20000
ValueCountFrequency (%)
85000 2
40.0%
20000 1
20.0%
197509 1
20.0%
220000 1
20.0%
2023-12-09T23:29:31.913492image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 15
55.6%
5 3
 
11.1%
2 3
 
11.1%
8 2
 
7.4%
9 2
 
7.4%
1 1
 
3.7%
7 1
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 27
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 15
55.6%
5 3
 
11.1%
2 3
 
11.1%
8 2
 
7.4%
9 2
 
7.4%
1 1
 
3.7%
7 1
 
3.7%

Most occurring scripts

ValueCountFrequency (%)
Common 27
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 15
55.6%
5 3
 
11.1%
2 3
 
11.1%
8 2
 
7.4%
9 2
 
7.4%
1 1
 
3.7%
7 1
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 15
55.6%
5 3
 
11.1%
2 3
 
11.1%
8 2
 
7.4%
9 2
 
7.4%
1 1
 
3.7%
7 1
 
3.7%
Distinct35
Distinct (%)94.6%
Missing963
Missing (%)96.3%
Memory size32.5 KiB
2023-12-09T23:29:32.167582image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.243243243
Min length4

Characters and Unicode

Total characters194
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)89.2%

Sample

1st row104407
2nd row4455
3rd row150000
4th row36300
5th row77000
ValueCountFrequency (%)
88500 2
 
5.4%
104407 2
 
5.4%
53000 1
 
2.7%
5728 1
 
2.7%
24548.8 1
 
2.7%
75447 1
 
2.7%
22630 1
 
2.7%
71965 1
 
2.7%
88000 1
 
2.7%
98290 1
 
2.7%
Other values (25) 25
67.6%
2023-12-09T23:29:32.552782image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 78
40.2%
5 20
 
10.3%
4 18
 
9.3%
1 15
 
7.7%
7 15
 
7.7%
8 12
 
6.2%
6 12
 
6.2%
2 10
 
5.2%
3 9
 
4.6%
9 4
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 193
99.5%
Other Punctuation 1
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 78
40.4%
5 20
 
10.4%
4 18
 
9.3%
1 15
 
7.8%
7 15
 
7.8%
8 12
 
6.2%
6 12
 
6.2%
2 10
 
5.2%
3 9
 
4.7%
9 4
 
2.1%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 194
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 78
40.2%
5 20
 
10.3%
4 18
 
9.3%
1 15
 
7.7%
7 15
 
7.7%
8 12
 
6.2%
6 12
 
6.2%
2 10
 
5.2%
3 9
 
4.6%
9 4
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 194
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 78
40.2%
5 20
 
10.3%
4 18
 
9.3%
1 15
 
7.7%
7 15
 
7.7%
8 12
 
6.2%
6 12
 
6.2%
2 10
 
5.2%
3 9
 
4.6%
9 4
 
2.1%
Distinct69
Distinct (%)89.6%
Missing923
Missing (%)92.3%
Memory size33.6 KiB
2023-12-09T23:29:32.862705image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length6
Mean length4.688311688
Min length1

Characters and Unicode

Total characters361
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique63 ?
Unique (%)81.8%

Sample

1st row7918
2nd row3054
3rd row37500
4th row82633
5th row82856
ValueCountFrequency (%)
0 4
 
5.2%
1500 2
 
2.6%
75100 2
 
2.6%
10000 2
 
2.6%
105000 2
 
2.6%
29566 2
 
2.6%
16800 1
 
1.3%
65500 1
 
1.3%
8000 1
 
1.3%
6113 1
 
1.3%
Other values (59) 59
76.6%
2023-12-09T23:29:33.320446image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 104
28.8%
1 55
15.2%
5 37
 
10.2%
2 33
 
9.1%
3 26
 
7.2%
8 26
 
7.2%
6 24
 
6.6%
9 23
 
6.4%
4 17
 
4.7%
7 15
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 360
99.7%
Other Punctuation 1
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 104
28.9%
1 55
15.3%
5 37
 
10.3%
2 33
 
9.2%
3 26
 
7.2%
8 26
 
7.2%
6 24
 
6.7%
9 23
 
6.4%
4 17
 
4.7%
7 15
 
4.2%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 361
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 104
28.8%
1 55
15.2%
5 37
 
10.2%
2 33
 
9.1%
3 26
 
7.2%
8 26
 
7.2%
6 24
 
6.6%
9 23
 
6.4%
4 17
 
4.7%
7 15
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 361
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 104
28.8%
1 55
15.2%
5 37
 
10.2%
2 33
 
9.1%
3 26
 
7.2%
8 26
 
7.2%
6 24
 
6.6%
9 23
 
6.4%
4 17
 
4.7%
7 15
 
4.2%
Distinct32
Distinct (%)54.2%
Missing941
Missing (%)94.1%
Memory size32.9 KiB
2023-12-09T23:29:33.540291image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length2
Mean length2.288135593
Min length1

Characters and Unicode

Total characters135
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)42.4%

Sample

1st row40
2nd row76
3rd row36
4th row40
5th row0
ValueCountFrequency (%)
0 8
 
13.6%
80 6
 
10.2%
40 5
 
8.5%
70 5
 
8.5%
50 5
 
8.5%
60 3
 
5.1%
84 2
 
3.4%
58.38 1
 
1.7%
71 1
 
1.7%
90 1
 
1.7%
Other values (22) 22
37.3%
2023-12-09T23:29:33.864130image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 35
25.9%
8 17
12.6%
6 14
 
10.4%
4 13
 
9.6%
5 12
 
8.9%
7 11
 
8.1%
1 9
 
6.7%
2 8
 
5.9%
. 6
 
4.4%
3 5
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 129
95.6%
Other Punctuation 6
 
4.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 35
27.1%
8 17
13.2%
6 14
 
10.9%
4 13
 
10.1%
5 12
 
9.3%
7 11
 
8.5%
1 9
 
7.0%
2 8
 
6.2%
3 5
 
3.9%
9 5
 
3.9%
Other Punctuation
ValueCountFrequency (%)
. 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 135
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 35
25.9%
8 17
12.6%
6 14
 
10.4%
4 13
 
9.6%
5 12
 
8.9%
7 11
 
8.1%
1 9
 
6.7%
2 8
 
5.9%
. 6
 
4.4%
3 5
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 135
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 35
25.9%
8 17
12.6%
6 14
 
10.4%
4 13
 
9.6%
5 12
 
8.9%
7 11
 
8.1%
1 9
 
6.7%
2 8
 
5.9%
. 6
 
4.4%
3 5
 
3.7%
Distinct25
Distinct (%)43.1%
Missing942
Missing (%)94.2%
Memory size32.9 KiB
2023-12-09T23:29:34.055128image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length1
Mean length1.620689655
Min length1

Characters and Unicode

Total characters94
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)17.2%

Sample

1st row1.6
2nd row2
3rd row0
4th row8
5th row0
ValueCountFrequency (%)
0 10
17.2%
10 4
 
6.9%
8 4
 
6.9%
1 3
 
5.2%
12 3
 
5.2%
9 3
 
5.2%
2 3
 
5.2%
6 3
 
5.2%
5 3
 
5.2%
3 2
 
3.4%
Other values (15) 20
34.5%
2023-12-09T23:29:34.357261image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 20
21.3%
1 20
21.3%
2 12
12.8%
5 11
11.7%
6 8
 
8.5%
8 7
 
7.4%
3 6
 
6.4%
4 4
 
4.3%
9 3
 
3.2%
7 2
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 93
98.9%
Other Punctuation 1
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 20
21.5%
1 20
21.5%
2 12
12.9%
5 11
11.8%
6 8
 
8.6%
8 7
 
7.5%
3 6
 
6.5%
4 4
 
4.3%
9 3
 
3.2%
7 2
 
2.2%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 94
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 20
21.3%
1 20
21.3%
2 12
12.8%
5 11
11.7%
6 8
 
8.5%
8 7
 
7.4%
3 6
 
6.4%
4 4
 
4.3%
9 3
 
3.2%
7 2
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 94
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 20
21.3%
1 20
21.3%
2 12
12.8%
5 11
11.7%
6 8
 
8.5%
8 7
 
7.4%
3 6
 
6.4%
4 4
 
4.3%
9 3
 
3.2%
7 2
 
2.1%
Distinct33
Distinct (%)56.9%
Missing942
Missing (%)94.2%
Memory size32.9 KiB
2023-12-09T23:29:34.556934image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length3
Mean length1.827586207
Min length1

Characters and Unicode

Total characters106
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)37.9%

Sample

1st row0
2nd row6
3rd row28
4th row15
5th row0
ValueCountFrequency (%)
0 9
 
15.5%
15 5
 
8.6%
4 4
 
6.9%
6 3
 
5.2%
12 3
 
5.2%
20 2
 
3.4%
8 2
 
3.4%
180 2
 
3.4%
30 2
 
3.4%
9 2
 
3.4%
Other values (23) 24
41.4%
2023-12-09T23:29:34.890695image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 22
20.8%
1 18
17.0%
2 13
12.3%
5 12
11.3%
3 10
9.4%
6 9
8.5%
4 8
 
7.5%
8 6
 
5.7%
9 3
 
2.8%
7 3
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 104
98.1%
Other Punctuation 2
 
1.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 22
21.2%
1 18
17.3%
2 13
12.5%
5 12
11.5%
3 10
9.6%
6 9
8.7%
4 8
 
7.7%
8 6
 
5.8%
9 3
 
2.9%
7 3
 
2.9%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 106
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 22
20.8%
1 18
17.0%
2 13
12.3%
5 12
11.3%
3 10
9.4%
6 9
8.5%
4 8
 
7.5%
8 6
 
5.7%
9 3
 
2.8%
7 3
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 106
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 22
20.8%
1 18
17.0%
2 13
12.3%
5 12
11.3%
3 10
9.4%
6 9
8.5%
4 8
 
7.5%
8 6
 
5.7%
9 3
 
2.8%
7 3
 
2.8%
Distinct2
Distinct (%)100.0%
Missing998
Missing (%)99.8%
Memory size31.4 KiB
2023-12-09T23:29:35.054736image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters12
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row115720
2nd row146865
ValueCountFrequency (%)
146865 1
50.0%
115720 1
50.0%
2023-12-09T23:29:35.322123image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 3
25.0%
6 2
16.7%
5 2
16.7%
4 1
 
8.3%
8 1
 
8.3%
7 1
 
8.3%
2 1
 
8.3%
0 1
 
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3
25.0%
6 2
16.7%
5 2
16.7%
4 1
 
8.3%
8 1
 
8.3%
7 1
 
8.3%
2 1
 
8.3%
0 1
 
8.3%

Most occurring scripts

ValueCountFrequency (%)
Common 12
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 3
25.0%
6 2
16.7%
5 2
16.7%
4 1
 
8.3%
8 1
 
8.3%
7 1
 
8.3%
2 1
 
8.3%
0 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3
25.0%
6 2
16.7%
5 2
16.7%
4 1
 
8.3%
8 1
 
8.3%
7 1
 
8.3%
2 1
 
8.3%
0 1
 
8.3%

pre_school_daycare_gross
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)50.0%
Missing998
Missing (%)99.8%
Memory size31.4 KiB
2023-12-09T23:29:35.461587image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters12
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row190000
2nd row190000
ValueCountFrequency (%)
190000 2
100.0%
2023-12-09T23:29:35.701041image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 8
66.7%
1 2
 
16.7%
9 2
 
16.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 8
66.7%
1 2
 
16.7%
9 2
 
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 12
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 8
66.7%
1 2
 
16.7%
9 2
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 8
66.7%
1 2
 
16.7%
9 2
 
16.7%
Distinct19
Distinct (%)90.5%
Missing979
Missing (%)97.9%
Memory size32.0 KiB
2023-12-09T23:29:35.896832image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.285714286
Min length3

Characters and Unicode

Total characters90
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)81.0%

Sample

1st row13799
2nd row4758
3rd row5000
4th row5000
5th row20000
ValueCountFrequency (%)
11244 2
 
9.5%
5000 2
 
9.5%
1872 1
 
4.8%
6562 1
 
4.8%
1534 1
 
4.8%
3359 1
 
4.8%
12300 1
 
4.8%
20000 1
 
4.8%
10283 1
 
4.8%
13799 1
 
4.8%
Other values (9) 9
42.9%
2023-12-09T23:29:36.232483image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 27
30.0%
5 12
13.3%
1 10
 
11.1%
2 9
 
10.0%
3 9
 
10.0%
4 8
 
8.9%
9 4
 
4.4%
8 4
 
4.4%
7 4
 
4.4%
6 3
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 90
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 27
30.0%
5 12
13.3%
1 10
 
11.1%
2 9
 
10.0%
3 9
 
10.0%
4 8
 
8.9%
9 4
 
4.4%
8 4
 
4.4%
7 4
 
4.4%
6 3
 
3.3%

Most occurring scripts

ValueCountFrequency (%)
Common 90
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 27
30.0%
5 12
13.3%
1 10
 
11.1%
2 9
 
10.0%
3 9
 
10.0%
4 8
 
8.9%
9 4
 
4.4%
8 4
 
4.4%
7 4
 
4.4%
6 3
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 27
30.0%
5 12
13.3%
1 10
 
11.1%
2 9
 
10.0%
3 9
 
10.0%
4 8
 
8.9%
9 4
 
4.4%
8 4
 
4.4%
7 4
 
4.4%
6 3
 
3.3%
Distinct6
Distinct (%)50.0%
Missing988
Missing (%)98.8%
Memory size31.7 KiB
2023-12-09T23:29:36.396297image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length6
Mean length5.5
Min length4

Characters and Unicode

Total characters66
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)25.0%

Sample

1st row190000
2nd row721396
3rd row190000
4th row120200
5th row120200
ValueCountFrequency (%)
120200 4
33.3%
84000 3
25.0%
190000 2
16.7%
5000 1
 
8.3%
721396 1
 
8.3%
51956 1
 
8.3%
2023-12-09T23:29:36.690853image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 32
48.5%
2 9
 
13.6%
1 8
 
12.1%
9 4
 
6.1%
8 3
 
4.5%
4 3
 
4.5%
5 3
 
4.5%
6 2
 
3.0%
7 1
 
1.5%
3 1
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 66
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 32
48.5%
2 9
 
13.6%
1 8
 
12.1%
9 4
 
6.1%
8 3
 
4.5%
4 3
 
4.5%
5 3
 
4.5%
6 2
 
3.0%
7 1
 
1.5%
3 1
 
1.5%

Most occurring scripts

ValueCountFrequency (%)
Common 66
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 32
48.5%
2 9
 
13.6%
1 8
 
12.1%
9 4
 
6.1%
8 3
 
4.5%
4 3
 
4.5%
5 3
 
4.5%
6 2
 
3.0%
7 1
 
1.5%
3 1
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 66
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 32
48.5%
2 9
 
13.6%
1 8
 
12.1%
9 4
 
6.1%
8 3
 
4.5%
4 3
 
4.5%
5 3
 
4.5%
6 2
 
3.0%
7 1
 
1.5%
3 1
 
1.5%

repair_services_vehicle_shoe
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1000
Missing (%)100.0%
Memory size7.9 KiB
Distinct12
Distinct (%)100.0%
Missing988
Missing (%)98.8%
Memory size31.7 KiB
2023-12-09T23:29:36.887311image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.416666667
Min length5

Characters and Unicode

Total characters65
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)100.0%

Sample

1st row55442
2nd row75000
3rd row122641
4th row130096
5th row350000
ValueCountFrequency (%)
97000 1
8.3%
66230 1
8.3%
200000 1
8.3%
130096 1
8.3%
67655 1
8.3%
122641 1
8.3%
75000 1
8.3%
350000 1
8.3%
55945 1
8.3%
70000 1
8.3%
Other values (2) 2
16.7%
2023-12-09T23:29:37.209287image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 24
36.9%
5 9
 
13.8%
6 7
 
10.8%
2 5
 
7.7%
4 5
 
7.7%
7 4
 
6.2%
3 4
 
6.2%
1 4
 
6.2%
9 3
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 65
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 24
36.9%
5 9
 
13.8%
6 7
 
10.8%
2 5
 
7.7%
4 5
 
7.7%
7 4
 
6.2%
3 4
 
6.2%
1 4
 
6.2%
9 3
 
4.6%

Most occurring scripts

ValueCountFrequency (%)
Common 65
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 24
36.9%
5 9
 
13.8%
6 7
 
10.8%
2 5
 
7.7%
4 5
 
7.7%
7 4
 
6.2%
3 4
 
6.2%
1 4
 
6.2%
9 3
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 65
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 24
36.9%
5 9
 
13.8%
6 7
 
10.8%
2 5
 
7.7%
4 5
 
7.7%
7 4
 
6.2%
3 4
 
6.2%
1 4
 
6.2%
9 3
 
4.6%
Distinct30
Distinct (%)83.3%
Missing964
Missing (%)96.4%
Memory size32.4 KiB
2023-12-09T23:29:37.435480image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.111111111
Min length1

Characters and Unicode

Total characters148
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)72.2%

Sample

1st row1704
2nd row3721
3rd row3721
4th row26155
5th row32526
ValueCountFrequency (%)
3721 3
 
8.3%
4200 3
 
8.3%
1704 2
 
5.6%
26155 2
 
5.6%
30000 1
 
2.8%
1000 1
 
2.8%
21291 1
 
2.8%
1429 1
 
2.8%
20000 1
 
2.8%
39539 1
 
2.8%
Other values (20) 20
55.6%
2023-12-09T23:29:37.787073image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 40
27.0%
2 23
15.5%
4 19
12.8%
1 17
11.5%
5 15
 
10.1%
3 11
 
7.4%
7 9
 
6.1%
8 5
 
3.4%
9 5
 
3.4%
6 4
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 148
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 40
27.0%
2 23
15.5%
4 19
12.8%
1 17
11.5%
5 15
 
10.1%
3 11
 
7.4%
7 9
 
6.1%
8 5
 
3.4%
9 5
 
3.4%
6 4
 
2.7%

Most occurring scripts

ValueCountFrequency (%)
Common 148
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 40
27.0%
2 23
15.5%
4 19
12.8%
1 17
11.5%
5 15
 
10.1%
3 11
 
7.4%
7 9
 
6.1%
8 5
 
3.4%
9 5
 
3.4%
6 4
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 148
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 40
27.0%
2 23
15.5%
4 19
12.8%
1 17
11.5%
5 15
 
10.1%
3 11
 
7.4%
7 9
 
6.1%
8 5
 
3.4%
9 5
 
3.4%
6 4
 
2.7%
Distinct11
Distinct (%)100.0%
Missing989
Missing (%)98.9%
Memory size31.7 KiB
2023-12-09T23:29:37.986215image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.454545455
Min length5

Characters and Unicode

Total characters60
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)100.0%

Sample

1st row240000
2nd row96000
3rd row67500
4th row126530
5th row84767
ValueCountFrequency (%)
62549 1
9.1%
66950 1
9.1%
126530 1
9.1%
240000 1
9.1%
67500 1
9.1%
113886 1
9.1%
175100 1
9.1%
96000 1
9.1%
255084 1
9.1%
61111 1
9.1%
2023-12-09T23:29:38.296921image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14
23.3%
6 9
15.0%
1 9
15.0%
5 7
11.7%
2 4
 
6.7%
4 4
 
6.7%
7 4
 
6.7%
8 4
 
6.7%
9 3
 
5.0%
3 2
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 14
23.3%
6 9
15.0%
1 9
15.0%
5 7
11.7%
2 4
 
6.7%
4 4
 
6.7%
7 4
 
6.7%
8 4
 
6.7%
9 3
 
5.0%
3 2
 
3.3%

Most occurring scripts

ValueCountFrequency (%)
Common 60
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 14
23.3%
6 9
15.0%
1 9
15.0%
5 7
11.7%
2 4
 
6.7%
4 4
 
6.7%
7 4
 
6.7%
8 4
 
6.7%
9 3
 
5.0%
3 2
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 60
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 14
23.3%
6 9
15.0%
1 9
15.0%
5 7
11.7%
2 4
 
6.7%
4 4
 
6.7%
7 4
 
6.7%
8 4
 
6.7%
9 3
 
5.0%
3 2
 
3.3%
Distinct16
Distinct (%)100.0%
Missing984
Missing (%)98.4%
Memory size31.9 KiB
2023-12-09T23:29:38.501381image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length5.5
Mean length5.5
Min length5

Characters and Unicode

Total characters88
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)100.0%

Sample

1st row111667
2nd row381993
3rd row504688
4th row98642
5th row87000
ValueCountFrequency (%)
131000 1
 
6.2%
188760 1
 
6.2%
98642 1
 
6.2%
70000 1
 
6.2%
504688 1
 
6.2%
87036 1
 
6.2%
111667 1
 
6.2%
95412 1
 
6.2%
156840 1
 
6.2%
87000 1
 
6.2%
Other values (6) 6
37.5%
2023-12-09T23:29:38.815120image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 21
23.9%
1 11
12.5%
8 11
12.5%
7 10
11.4%
6 9
10.2%
9 6
 
6.8%
4 6
 
6.8%
5 6
 
6.8%
3 4
 
4.5%
2 4
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 88
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 21
23.9%
1 11
12.5%
8 11
12.5%
7 10
11.4%
6 9
10.2%
9 6
 
6.8%
4 6
 
6.8%
5 6
 
6.8%
3 4
 
4.5%
2 4
 
4.5%

Most occurring scripts

ValueCountFrequency (%)
Common 88
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 21
23.9%
1 11
12.5%
8 11
12.5%
7 10
11.4%
6 9
10.2%
9 6
 
6.8%
4 6
 
6.8%
5 6
 
6.8%
3 4
 
4.5%
2 4
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 88
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 21
23.9%
1 11
12.5%
8 11
12.5%
7 10
11.4%
6 9
10.2%
9 6
 
6.8%
4 6
 
6.8%
5 6
 
6.8%
3 4
 
4.5%
2 4
 
4.5%
Distinct2
Distinct (%)100.0%
Missing998
Missing (%)99.8%
Memory size31.4 KiB
2023-12-09T23:29:38.964735image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters10
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row31868
2nd row95092
ValueCountFrequency (%)
31868 1
50.0%
95092 1
50.0%
2023-12-09T23:29:39.214763image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 2
20.0%
9 2
20.0%
3 1
10.0%
1 1
10.0%
6 1
10.0%
5 1
10.0%
0 1
10.0%
2 1
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 2
20.0%
9 2
20.0%
3 1
10.0%
1 1
10.0%
6 1
10.0%
5 1
10.0%
0 1
10.0%
2 1
10.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 2
20.0%
9 2
20.0%
3 1
10.0%
1 1
10.0%
6 1
10.0%
5 1
10.0%
0 1
10.0%
2 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 2
20.0%
9 2
20.0%
3 1
10.0%
1 1
10.0%
6 1
10.0%
5 1
10.0%
0 1
10.0%
2 1
10.0%

wholesale_club_supercenter
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1000
Missing (%)100.0%
Memory size7.9 KiB
Distinct6
Distinct (%)100.0%
Missing994
Missing (%)99.4%
Memory size31.6 KiB
2023-12-09T23:29:39.399775image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters30
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st row28086
2nd row15633
3rd row37846
4th row20000
5th row19000
ValueCountFrequency (%)
37846 1
16.7%
20000 1
16.7%
28086 1
16.7%
15633 1
16.7%
19000 1
16.7%
27610 1
16.7%
2023-12-09T23:29:39.698462image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9
30.0%
6 4
13.3%
3 3
 
10.0%
8 3
 
10.0%
2 3
 
10.0%
1 3
 
10.0%
7 2
 
6.7%
4 1
 
3.3%
5 1
 
3.3%
9 1
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 30
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9
30.0%
6 4
13.3%
3 3
 
10.0%
8 3
 
10.0%
2 3
 
10.0%
1 3
 
10.0%
7 2
 
6.7%
4 1
 
3.3%
5 1
 
3.3%
9 1
 
3.3%

Most occurring scripts

ValueCountFrequency (%)
Common 30
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9
30.0%
6 4
13.3%
3 3
 
10.0%
8 3
 
10.0%
2 3
 
10.0%
1 3
 
10.0%
7 2
 
6.7%
4 1
 
3.3%
5 1
 
3.3%
9 1
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9
30.0%
6 4
13.3%
3 3
 
10.0%
8 3
 
10.0%
2 3
 
10.0%
1 3
 
10.0%
7 2
 
6.7%
4 1
 
3.3%
5 1
 
3.3%
9 1
 
3.3%
Distinct73
Distinct (%)83.9%
Missing913
Missing (%)91.3%
Memory size33.9 KiB
2023-12-09T23:29:39.996856image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length5
Mean length4.448275862
Min length1

Characters and Unicode

Total characters387
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique62 ?
Unique (%)71.3%

Sample

1st row8092
2nd row60015
3rd row75521.8
4th row2790
5th row14700
ValueCountFrequency (%)
10000 4
 
4.6%
2000 3
 
3.4%
1500 2
 
2.3%
88151 2
 
2.3%
7500 2
 
2.3%
7300 2
 
2.3%
20000 2
 
2.3%
52888 2
 
2.3%
15727 2
 
2.3%
44948 2
 
2.3%
Other values (63) 64
73.6%
2023-12-09T23:29:40.434307image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 117
30.2%
5 39
 
10.1%
2 38
 
9.8%
1 37
 
9.6%
8 37
 
9.6%
3 30
 
7.8%
7 28
 
7.2%
4 24
 
6.2%
9 20
 
5.2%
6 16
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 386
99.7%
Other Punctuation 1
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 117
30.3%
5 39
 
10.1%
2 38
 
9.8%
1 37
 
9.6%
8 37
 
9.6%
3 30
 
7.8%
7 28
 
7.3%
4 24
 
6.2%
9 20
 
5.2%
6 16
 
4.1%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 387
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 117
30.2%
5 39
 
10.1%
2 38
 
9.8%
1 37
 
9.6%
8 37
 
9.6%
3 30
 
7.8%
7 28
 
7.2%
4 24
 
6.2%
9 20
 
5.2%
6 16
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 387
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 117
30.2%
5 39
 
10.1%
2 38
 
9.8%
1 37
 
9.6%
8 37
 
9.6%
3 30
 
7.8%
7 28
 
7.2%
4 24
 
6.2%
9 20
 
5.2%
6 16
 
4.1%
Distinct22
Distinct (%)75.9%
Missing971
Missing (%)97.1%
Memory size32.3 KiB
2023-12-09T23:29:40.668034image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length8
Median length7
Mean length6
Min length1

Characters and Unicode

Total characters174
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)58.6%

Sample

1st row10.56338
2nd row8.06235
3rd row8.06235
4th row1.91168
5th row8.06235
ValueCountFrequency (%)
1 3
 
10.3%
8.06235 3
 
10.3%
1.91168 2
 
6.9%
6.66667 2
 
6.9%
10.56338 2
 
6.9%
3.63636 1
 
3.4%
1.2 1
 
3.4%
6.17962 1
 
3.4%
5.69395 1
 
3.4%
6.44933 1
 
3.4%
Other values (12) 12
41.4%
2023-12-09T23:29:41.020719image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 27
15.5%
1 25
14.4%
. 25
14.4%
3 22
12.6%
5 15
8.6%
8 14
8.0%
2 13
7.5%
9 12
6.9%
0 9
 
5.2%
7 7
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 149
85.6%
Other Punctuation 25
 
14.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 27
18.1%
1 25
16.8%
3 22
14.8%
5 15
10.1%
8 14
9.4%
2 13
8.7%
9 12
8.1%
0 9
 
6.0%
7 7
 
4.7%
4 5
 
3.4%
Other Punctuation
ValueCountFrequency (%)
. 25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 174
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 27
15.5%
1 25
14.4%
. 25
14.4%
3 22
12.6%
5 15
8.6%
8 14
8.0%
2 13
7.5%
9 12
6.9%
0 9
 
5.2%
7 7
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 174
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 27
15.5%
1 25
14.4%
. 25
14.4%
3 22
12.6%
5 15
8.6%
8 14
8.0%
2 13
7.5%
9 12
6.9%
0 9
 
5.2%
7 7
 
4.0%
Distinct21
Distinct (%)70.0%
Missing970
Missing (%)97.0%
Memory size32.2 KiB
2023-12-09T23:29:41.226515image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.5
Min length1

Characters and Unicode

Total characters75
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)43.3%

Sample

1st row57
2nd row61
3rd row61
4th row79.46
5th row61
ValueCountFrequency (%)
61 3
 
10.0%
57 2
 
6.7%
40 2
 
6.7%
60 2
 
6.7%
168 2
 
6.7%
70 2
 
6.7%
79.46 2
 
6.7%
50 2
 
6.7%
0 1
 
3.3%
90 1
 
3.3%
Other values (11) 11
36.7%
2023-12-09T23:29:41.557267image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 13
17.3%
0 11
14.7%
5 10
13.3%
7 8
10.7%
4 8
10.7%
1 7
9.3%
8 6
8.0%
. 5
 
6.7%
9 4
 
5.3%
2 2
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 70
93.3%
Other Punctuation 5
 
6.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 13
18.6%
0 11
15.7%
5 10
14.3%
7 8
11.4%
4 8
11.4%
1 7
10.0%
8 6
8.6%
9 4
 
5.7%
2 2
 
2.9%
3 1
 
1.4%
Other Punctuation
ValueCountFrequency (%)
. 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 75
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 13
17.3%
0 11
14.7%
5 10
13.3%
7 8
10.7%
4 8
10.7%
1 7
9.3%
8 6
8.0%
. 5
 
6.7%
9 4
 
5.3%
2 2
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 75
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 13
17.3%
0 11
14.7%
5 10
13.3%
7 8
10.7%
4 8
10.7%
1 7
9.3%
8 6
8.0%
. 5
 
6.7%
9 4
 
5.3%
2 2
 
2.7%

retail_store_walk_in
Text

MISSING 

Distinct13
Distinct (%)15.3%
Missing915
Missing (%)91.5%
Memory size33.6 KiB
2023-12-09T23:29:41.716338image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length1
Mean length1.847058824
Min length1

Characters and Unicode

Total characters157
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)12.9%

Sample

1st row0
2nd row0.04999
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 72
84.7%
0.01891 2
 
2.4%
0.1969 1
 
1.2%
0.14815 1
 
1.2%
0.5 1
 
1.2%
0.04999 1
 
1.2%
0.28841 1
 
1.2%
0.22492 1
 
1.2%
0.16667 1
 
1.2%
0.20751 1
 
1.2%
Other values (3) 3
 
3.5%
2023-12-09T23:29:41.998097image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 91
58.0%
. 13
 
8.3%
1 11
 
7.0%
2 10
 
6.4%
9 8
 
5.1%
8 6
 
3.8%
6 5
 
3.2%
7 5
 
3.2%
4 4
 
2.5%
5 3
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 144
91.7%
Other Punctuation 13
 
8.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 91
63.2%
1 11
 
7.6%
2 10
 
6.9%
9 8
 
5.6%
8 6
 
4.2%
6 5
 
3.5%
7 5
 
3.5%
4 4
 
2.8%
5 3
 
2.1%
3 1
 
0.7%
Other Punctuation
ValueCountFrequency (%)
. 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 157
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 91
58.0%
. 13
 
8.3%
1 11
 
7.0%
2 10
 
6.4%
9 8
 
5.1%
8 6
 
3.8%
6 5
 
3.2%
7 5
 
3.2%
4 4
 
2.5%
5 3
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 157
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 91
58.0%
. 13
 
8.3%
1 11
 
7.0%
2 10
 
6.4%
9 8
 
5.1%
8 6
 
3.8%
6 5
 
3.2%
7 5
 
3.2%
4 4
 
2.5%
5 3
 
1.9%
Distinct16
Distinct (%)18.6%
Missing914
Missing (%)91.4%
Memory size33.7 KiB
2023-12-09T23:29:42.146836image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.825581395
Min length1

Characters and Unicode

Total characters243
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)12.8%

Sample

1st row90
2nd row80.33
3rd row100
4th row100
5th row100
ValueCountFrequency (%)
100 58
67.4%
0 8
 
9.3%
60 5
 
5.8%
50 2
 
2.3%
90 2
 
2.3%
88.72 1
 
1.2%
80 1
 
1.2%
60.87 1
 
1.2%
84.62 1
 
1.2%
57.88 1
 
1.2%
Other values (6) 6
 
7.0%
2023-12-09T23:29:42.431771image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 140
57.6%
1 58
23.9%
8 9
 
3.7%
6 7
 
2.9%
. 7
 
2.9%
7 6
 
2.5%
5 4
 
1.6%
2 4
 
1.6%
9 3
 
1.2%
3 3
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 236
97.1%
Other Punctuation 7
 
2.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 140
59.3%
1 58
24.6%
8 9
 
3.8%
6 7
 
3.0%
7 6
 
2.5%
5 4
 
1.7%
2 4
 
1.7%
9 3
 
1.3%
3 3
 
1.3%
4 2
 
0.8%
Other Punctuation
ValueCountFrequency (%)
. 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 243
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 140
57.6%
1 58
23.9%
8 9
 
3.7%
6 7
 
2.9%
. 7
 
2.9%
7 6
 
2.5%
5 4
 
1.6%
2 4
 
1.6%
9 3
 
1.2%
3 3
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 243
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 140
57.6%
1 58
23.9%
8 9
 
3.7%
6 7
 
2.9%
. 7
 
2.9%
7 6
 
2.5%
5 4
 
1.6%
2 4
 
1.6%
9 3
 
1.2%
3 3
 
1.2%
Distinct28
Distinct (%)32.9%
Missing915
Missing (%)91.5%
Memory size33.7 KiB
2023-12-09T23:29:42.628063image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length1
Mean length3.082352941
Min length1

Characters and Unicode

Total characters262
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)27.1%

Sample

1st row0
2nd row0.06665
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 54
63.5%
0.13236 2
 
2.4%
0.13699 2
 
2.4%
0.0488 2
 
2.4%
0.08899 2
 
2.4%
0.0631 1
 
1.2%
0.11246 1
 
1.2%
0.125 1
 
1.2%
0.75 1
 
1.2%
0.03728 1
 
1.2%
Other values (18) 18
 
21.2%
2023-12-09T23:29:42.950088image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 90
34.4%
. 31
 
11.8%
3 22
 
8.4%
1 21
 
8.0%
8 19
 
7.3%
6 17
 
6.5%
7 15
 
5.7%
5 14
 
5.3%
9 12
 
4.6%
2 11
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 231
88.2%
Other Punctuation 31
 
11.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 90
39.0%
3 22
 
9.5%
1 21
 
9.1%
8 19
 
8.2%
6 17
 
7.4%
7 15
 
6.5%
5 14
 
6.1%
9 12
 
5.2%
2 11
 
4.8%
4 10
 
4.3%
Other Punctuation
ValueCountFrequency (%)
. 31
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 262
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 90
34.4%
. 31
 
11.8%
3 22
 
8.4%
1 21
 
8.0%
8 19
 
7.3%
6 17
 
6.5%
7 15
 
5.7%
5 14
 
5.3%
9 12
 
4.6%
2 11
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 262
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 90
34.4%
. 31
 
11.8%
3 22
 
8.4%
1 21
 
8.0%
8 19
 
7.3%
6 17
 
6.5%
7 15
 
5.7%
5 14
 
5.3%
9 12
 
4.6%
2 11
 
4.2%
Distinct6
Distinct (%)7.0%
Missing914
Missing (%)91.4%
Memory size33.6 KiB
2023-12-09T23:29:43.075799image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters86
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)2.3%

Sample

1st row0
2nd row3
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 73
84.9%
1 6
 
7.0%
2 3
 
3.5%
4 2
 
2.3%
3 1
 
1.2%
9 1
 
1.2%
2023-12-09T23:29:43.298242image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 73
84.9%
1 6
 
7.0%
2 3
 
3.5%
4 2
 
2.3%
3 1
 
1.2%
9 1
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 86
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 73
84.9%
1 6
 
7.0%
2 3
 
3.5%
4 2
 
2.3%
3 1
 
1.2%
9 1
 
1.2%

Most occurring scripts

ValueCountFrequency (%)
Common 86
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 73
84.9%
1 6
 
7.0%
2 3
 
3.5%
4 2
 
2.3%
3 1
 
1.2%
9 1
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 86
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 73
84.9%
1 6
 
7.0%
2 3
 
3.5%
4 2
 
2.3%
3 1
 
1.2%
9 1
 
1.2%
Distinct14
Distinct (%)16.3%
Missing914
Missing (%)91.4%
Memory size33.6 KiB
2023-12-09T23:29:43.428882image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.11627907
Min length1

Characters and Unicode

Total characters96
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)8.1%

Sample

1st row0
2nd row4
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 55
64.0%
1 8
 
9.3%
2 5
 
5.8%
4 5
 
5.8%
10 2
 
2.3%
4.3 2
 
2.3%
7 2
 
2.3%
15 1
 
1.2%
17 1
 
1.2%
22 1
 
1.2%
Other values (4) 4
 
4.7%
2023-12-09T23:29:43.686997image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 57
59.4%
1 13
 
13.5%
2 8
 
8.3%
4 7
 
7.3%
3 3
 
3.1%
7 3
 
3.1%
. 2
 
2.1%
5 2
 
2.1%
8 1
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 94
97.9%
Other Punctuation 2
 
2.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 57
60.6%
1 13
 
13.8%
2 8
 
8.5%
4 7
 
7.4%
3 3
 
3.2%
7 3
 
3.2%
5 2
 
2.1%
8 1
 
1.1%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 96
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 57
59.4%
1 13
 
13.5%
2 8
 
8.3%
4 7
 
7.3%
3 3
 
3.1%
7 3
 
3.1%
. 2
 
2.1%
5 2
 
2.1%
8 1
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 96
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 57
59.4%
1 13
 
13.5%
2 8
 
8.3%
4 7
 
7.3%
3 3
 
3.1%
7 3
 
3.1%
. 2
 
2.1%
5 2
 
2.1%
8 1
 
1.0%
Distinct43
Distinct (%)65.2%
Missing934
Missing (%)93.4%
Memory size33.2 KiB
2023-12-09T23:29:43.912859image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length5
Mean length3.727272727
Min length1

Characters and Unicode

Total characters246
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)57.6%

Sample

1st row65226
2nd row73500
3rd row10000
4th row10000
5th row5000
ValueCountFrequency (%)
0 19
28.8%
5000 3
 
4.5%
20000 2
 
3.0%
31625 2
 
3.0%
10000 2
 
3.0%
294656 1
 
1.5%
717154 1
 
1.5%
34500 1
 
1.5%
67864 1
 
1.5%
1000 1
 
1.5%
Other values (33) 33
50.0%
2023-12-09T23:29:44.270595image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 84
34.1%
1 24
 
9.8%
7 21
 
8.5%
5 20
 
8.1%
3 20
 
8.1%
2 19
 
7.7%
6 19
 
7.7%
8 16
 
6.5%
9 13
 
5.3%
4 10
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 246
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 84
34.1%
1 24
 
9.8%
7 21
 
8.5%
5 20
 
8.1%
3 20
 
8.1%
2 19
 
7.7%
6 19
 
7.7%
8 16
 
6.5%
9 13
 
5.3%
4 10
 
4.1%

Most occurring scripts

ValueCountFrequency (%)
Common 246
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 84
34.1%
1 24
 
9.8%
7 21
 
8.5%
5 20
 
8.1%
3 20
 
8.1%
2 19
 
7.7%
6 19
 
7.7%
8 16
 
6.5%
9 13
 
5.3%
4 10
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 246
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 84
34.1%
1 24
 
9.8%
7 21
 
8.5%
5 20
 
8.1%
3 20
 
8.1%
2 19
 
7.7%
6 19
 
7.7%
8 16
 
6.5%
9 13
 
5.3%
4 10
 
4.1%
Distinct18
Distinct (%)27.3%
Missing934
Missing (%)93.4%
Memory size33.1 KiB
2023-12-09T23:29:44.444534image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length1
Mean length2.46969697
Min length1

Characters and Unicode

Total characters163
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)19.7%

Sample

1st row0
2nd row0
3rd row0
4th row10000
5th row5000
ValueCountFrequency (%)
0 41
62.1%
58000 5
 
7.6%
5000 3
 
4.5%
101887 2
 
3.0%
90723 2
 
3.0%
25381 1
 
1.5%
10000 1
 
1.5%
2000 1
 
1.5%
1000 1
 
1.5%
25000 1
 
1.5%
Other values (8) 8
 
12.1%
2023-12-09T23:29:44.726566image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 94
57.7%
5 14
 
8.6%
1 11
 
6.7%
8 10
 
6.1%
2 10
 
6.1%
7 7
 
4.3%
9 7
 
4.3%
3 6
 
3.7%
6 2
 
1.2%
4 2
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 163
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 94
57.7%
5 14
 
8.6%
1 11
 
6.7%
8 10
 
6.1%
2 10
 
6.1%
7 7
 
4.3%
9 7
 
4.3%
3 6
 
3.7%
6 2
 
1.2%
4 2
 
1.2%

Most occurring scripts

ValueCountFrequency (%)
Common 163
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 94
57.7%
5 14
 
8.6%
1 11
 
6.7%
8 10
 
6.1%
2 10
 
6.1%
7 7
 
4.3%
9 7
 
4.3%
3 6
 
3.7%
6 2
 
1.2%
4 2
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 163
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 94
57.7%
5 14
 
8.6%
1 11
 
6.7%
8 10
 
6.1%
2 10
 
6.1%
7 7
 
4.3%
9 7
 
4.3%
3 6
 
3.7%
6 2
 
1.2%
4 2
 
1.2%
Distinct44
Distinct (%)83.0%
Missing947
Missing (%)94.7%
Memory size33.0 KiB
2023-12-09T23:29:44.992306image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.660377358
Min length5

Characters and Unicode

Total characters300
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)69.8%

Sample

1st row125000
2nd row50000
3rd row50000
4th row120780
5th row112900
ValueCountFrequency (%)
90633 3
 
5.7%
200000 3
 
5.7%
55411 2
 
3.8%
50000 2
 
3.8%
187000 2
 
3.8%
85900 2
 
3.8%
65000 2
 
3.8%
126529 1
 
1.9%
153761 1
 
1.9%
893750 1
 
1.9%
Other values (34) 34
64.2%
2023-12-09T23:29:45.398203image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 96
32.0%
1 40
13.3%
5 36
 
12.0%
2 27
 
9.0%
3 23
 
7.7%
9 19
 
6.3%
8 16
 
5.3%
6 15
 
5.0%
4 15
 
5.0%
7 13
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 300
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 96
32.0%
1 40
13.3%
5 36
 
12.0%
2 27
 
9.0%
3 23
 
7.7%
9 19
 
6.3%
8 16
 
5.3%
6 15
 
5.0%
4 15
 
5.0%
7 13
 
4.3%

Most occurring scripts

ValueCountFrequency (%)
Common 300
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 96
32.0%
1 40
13.3%
5 36
 
12.0%
2 27
 
9.0%
3 23
 
7.7%
9 19
 
6.3%
8 16
 
5.3%
6 15
 
5.0%
4 15
 
5.0%
7 13
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 300
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 96
32.0%
1 40
13.3%
5 36
 
12.0%
2 27
 
9.0%
3 23
 
7.7%
9 19
 
6.3%
8 16
 
5.3%
6 15
 
5.0%
4 15
 
5.0%
7 13
 
4.3%
Distinct20
Distinct (%)64.5%
Missing969
Missing (%)96.9%
Memory size32.2 KiB
2023-12-09T23:29:45.586601image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.838709677
Min length1

Characters and Unicode

Total characters88
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)45.2%

Sample

1st row700
2nd row0
3rd row1000
4th row0
5th row0
ValueCountFrequency (%)
0 6
19.4%
700 3
 
9.7%
410 2
 
6.5%
425 2
 
6.5%
800 2
 
6.5%
100 2
 
6.5%
1951 1
 
3.2%
1000 1
 
3.2%
450 1
 
3.2%
1200 1
 
3.2%
Other values (10) 10
32.3%
2023-12-09T23:29:45.886274image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 40
45.5%
5 11
 
12.5%
1 9
 
10.2%
4 8
 
9.1%
2 8
 
9.1%
7 4
 
4.5%
8 3
 
3.4%
9 3
 
3.4%
6 2
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 88
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 40
45.5%
5 11
 
12.5%
1 9
 
10.2%
4 8
 
9.1%
2 8
 
9.1%
7 4
 
4.5%
8 3
 
3.4%
9 3
 
3.4%
6 2
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 88
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 40
45.5%
5 11
 
12.5%
1 9
 
10.2%
4 8
 
9.1%
2 8
 
9.1%
7 4
 
4.5%
8 3
 
3.4%
9 3
 
3.4%
6 2
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 88
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 40
45.5%
5 11
 
12.5%
1 9
 
10.2%
4 8
 
9.1%
2 8
 
9.1%
7 4
 
4.5%
8 3
 
3.4%
9 3
 
3.4%
6 2
 
2.3%
Distinct46
Distinct (%)86.8%
Missing947
Missing (%)94.7%
Memory size33.0 KiB
2023-12-09T23:29:46.149788image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.358490566
Min length1

Characters and Unicode

Total characters337
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)75.5%

Sample

1st row1.344
2nd row1.38
3rd row1.78
4th row0.61268
5th row1.95004
ValueCountFrequency (%)
2.73631 3
 
5.7%
2.24599 2
 
3.8%
2.43634 2
 
3.8%
1.95 2
 
3.8%
2.15367 2
 
3.8%
0.73846 2
 
3.8%
2.50845 1
 
1.9%
1.344 1
 
1.9%
1.40498 1
 
1.9%
0.61268 1
 
1.9%
Other values (36) 36
67.9%
2023-12-09T23:29:46.541982image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 52
15.4%
1 50
14.8%
2 37
11.0%
3 32
9.5%
0 28
8.3%
4 26
7.7%
6 24
7.1%
8 24
7.1%
7 23
6.8%
9 21
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 285
84.6%
Other Punctuation 52
 
15.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 50
17.5%
2 37
13.0%
3 32
11.2%
0 28
9.8%
4 26
9.1%
6 24
8.4%
8 24
8.4%
7 23
8.1%
9 21
7.4%
5 20
 
7.0%
Other Punctuation
ValueCountFrequency (%)
. 52
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 337
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 52
15.4%
1 50
14.8%
2 37
11.0%
3 32
9.5%
0 28
8.3%
4 26
7.7%
6 24
7.1%
8 24
7.1%
7 23
6.8%
9 21
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 337
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 52
15.4%
1 50
14.8%
2 37
11.0%
3 32
9.5%
0 28
8.3%
4 26
7.7%
6 24
7.1%
8 24
7.1%
7 23
6.8%
9 21
6.2%
Distinct44
Distinct (%)83.0%
Missing947
Missing (%)94.7%
Memory size33.0 KiB
2023-12-09T23:29:46.806795image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.20754717
Min length1

Characters and Unicode

Total characters329
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)71.7%

Sample

1st row2
2nd row0.28
3rd row0.4
4th row0.19871
5th row0.32002
ValueCountFrequency (%)
0.32 4
 
7.5%
0.33101 3
 
5.7%
0.45117 2
 
3.8%
0.53846 2
 
3.8%
0.32596 2
 
3.8%
0.26738 2
 
3.8%
0.68125 1
 
1.9%
0.50764 1
 
1.9%
0.6 1
 
1.9%
1.22308 1
 
1.9%
Other values (34) 34
64.2%
2023-12-09T23:29:48.135847image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 60
18.2%
. 51
15.5%
3 34
10.3%
1 29
8.8%
4 26
7.9%
2 24
 
7.3%
5 24
 
7.3%
7 23
 
7.0%
8 23
 
7.0%
6 20
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 278
84.5%
Other Punctuation 51
 
15.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 60
21.6%
3 34
12.2%
1 29
10.4%
4 26
9.4%
2 24
 
8.6%
5 24
 
8.6%
7 23
 
8.3%
8 23
 
8.3%
6 20
 
7.2%
9 15
 
5.4%
Other Punctuation
ValueCountFrequency (%)
. 51
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 329
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 60
18.2%
. 51
15.5%
3 34
10.3%
1 29
8.8%
4 26
7.9%
2 24
 
7.3%
5 24
 
7.3%
7 23
 
7.0%
8 23
 
7.0%
6 20
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 329
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 60
18.2%
. 51
15.5%
3 34
10.3%
1 29
8.8%
4 26
7.9%
2 24
 
7.3%
5 24
 
7.3%
7 23
 
7.0%
8 23
 
7.0%
6 20
 
6.1%
Distinct8
Distinct (%)15.1%
Missing947
Missing (%)94.7%
Memory size32.8 KiB
2023-12-09T23:29:48.281460image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.679245283
Min length1

Characters and Unicode

Total characters142
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)9.4%

Sample

1st row100
2nd row100
3rd row100
4th row80
5th row100
ValueCountFrequency (%)
100 35
66.0%
90 10
 
18.9%
80 3
 
5.7%
50 1
 
1.9%
60 1
 
1.9%
70 1
 
1.9%
0 1
 
1.9%
92.4 1
 
1.9%
2023-12-09T23:29:48.542478image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 87
61.3%
1 35
24.6%
9 11
 
7.7%
8 3
 
2.1%
5 1
 
0.7%
6 1
 
0.7%
7 1
 
0.7%
2 1
 
0.7%
. 1
 
0.7%
4 1
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 141
99.3%
Other Punctuation 1
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 87
61.7%
1 35
24.8%
9 11
 
7.8%
8 3
 
2.1%
5 1
 
0.7%
6 1
 
0.7%
7 1
 
0.7%
2 1
 
0.7%
4 1
 
0.7%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 142
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 87
61.3%
1 35
24.6%
9 11
 
7.7%
8 3
 
2.1%
5 1
 
0.7%
6 1
 
0.7%
7 1
 
0.7%
2 1
 
0.7%
. 1
 
0.7%
4 1
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 142
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 87
61.3%
1 35
24.6%
9 11
 
7.7%
8 3
 
2.1%
5 1
 
0.7%
6 1
 
0.7%
7 1
 
0.7%
2 1
 
0.7%
. 1
 
0.7%
4 1
 
0.7%

estimated_data_flag_1
Text

MISSING 

Distinct2
Distinct (%)40.0%
Missing995
Missing (%)99.5%
Memory size31.5 KiB
2023-12-09T23:29:48.681474image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.8
Min length4

Characters and Unicode

Total characters24
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)20.0%

Sample

1st rowfalse
2nd rowfalse
3rd rowfalse
4th rowtrue
5th rowfalse
ValueCountFrequency (%)
false 4
80.0%
true 1
 
20.0%
2023-12-09T23:29:48.925930image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 5
20.8%
f 4
16.7%
a 4
16.7%
l 4
16.7%
s 4
16.7%
t 1
 
4.2%
r 1
 
4.2%
u 1
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 24
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 5
20.8%
f 4
16.7%
a 4
16.7%
l 4
16.7%
s 4
16.7%
t 1
 
4.2%
r 1
 
4.2%
u 1
 
4.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 24
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 5
20.8%
f 4
16.7%
a 4
16.7%
l 4
16.7%
s 4
16.7%
t 1
 
4.2%
r 1
 
4.2%
u 1
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 5
20.8%
f 4
16.7%
a 4
16.7%
l 4
16.7%
s 4
16.7%
t 1
 
4.2%
r 1
 
4.2%
u 1
 
4.2%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size57.8 KiB
2023-12-09T23:29:49.052670image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length14
Median length2
Mean length2.012
Min length2

Characters and Unicode

Total characters2012
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st rowOk
2nd rowOk
3rd rowOk
4th rowOk
5th rowOk
ValueCountFrequency (%)
ok 999
99.8%
possible 1
 
0.1%
issue 1
 
0.1%
2023-12-09T23:29:49.298817image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
O 999
49.7%
k 999
49.7%
s 4
 
0.2%
e 2
 
0.1%
P 1
 
< 0.1%
o 1
 
< 0.1%
i 1
 
< 0.1%
b 1
 
< 0.1%
l 1
 
< 0.1%
1
 
< 0.1%
Other values (2) 2
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1010
50.2%
Uppercase Letter 1001
49.8%
Space Separator 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
k 999
98.9%
s 4
 
0.4%
e 2
 
0.2%
o 1
 
0.1%
i 1
 
0.1%
b 1
 
0.1%
l 1
 
0.1%
u 1
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
O 999
99.8%
P 1
 
0.1%
I 1
 
0.1%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2011
> 99.9%
Common 1
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
O 999
49.7%
k 999
49.7%
s 4
 
0.2%
e 2
 
0.1%
P 1
 
< 0.1%
o 1
 
< 0.1%
i 1
 
< 0.1%
b 1
 
< 0.1%
l 1
 
< 0.1%
I 1
 
< 0.1%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2012
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
O 999
49.7%
k 999
49.7%
s 4
 
0.2%
e 2
 
0.1%
P 1
 
< 0.1%
o 1
 
< 0.1%
i 1
 
< 0.1%
b 1
 
< 0.1%
l 1
 
< 0.1%
1
 
< 0.1%
Other values (2) 2
 
0.1%
Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size57.7 KiB
2023-12-09T23:29:49.408289image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2000
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowOk
2nd rowOk
3rd rowOk
4th rowOk
5th rowOk
ValueCountFrequency (%)
ok 1000
100.0%
2023-12-09T23:29:49.616991image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
O 1000
50.0%
k 1000
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1000
50.0%
Lowercase Letter 1000
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
O 1000
100.0%
Lowercase Letter
ValueCountFrequency (%)
k 1000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2000
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
O 1000
50.0%
k 1000
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
O 1000
50.0%
k 1000
50.0%
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size59.9 KiB
2023-12-09T23:29:49.759013image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length33
Median length2
Mean length4.239
Min length2

Characters and Unicode

Total characters4239
Distinct characters23
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowOk
2nd rowOk
3rd rowOk
4th rowOk
5th rowOk
ValueCountFrequency (%)
ok 872
68.3%
possible 91
 
7.1%
issue 91
 
7.1%
unable 37
 
2.9%
to 37
 
2.9%
check 37
 
2.9%
not 37
 
2.9%
enough 37
 
2.9%
data 37
 
2.9%
2023-12-09T23:29:50.015556image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
k 909
21.4%
O 872
20.6%
s 364
8.6%
e 293
 
6.9%
276
 
6.5%
o 202
 
4.8%
l 128
 
3.0%
u 128
 
3.0%
b 128
 
3.0%
n 111
 
2.6%
Other values (13) 828
19.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2761
65.1%
Uppercase Letter 1128
26.6%
Space Separator 276
 
6.5%
Open Punctuation 37
 
0.9%
Close Punctuation 37
 
0.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
k 909
32.9%
s 364
13.2%
e 293
 
10.6%
o 202
 
7.3%
l 128
 
4.6%
u 128
 
4.6%
b 128
 
4.6%
n 111
 
4.0%
a 111
 
4.0%
t 111
 
4.0%
Other values (5) 276
 
10.0%
Uppercase Letter
ValueCountFrequency (%)
O 872
77.3%
I 91
 
8.1%
P 91
 
8.1%
U 37
 
3.3%
C 37
 
3.3%
Space Separator
ValueCountFrequency (%)
276
100.0%
Open Punctuation
ValueCountFrequency (%)
( 37
100.0%
Close Punctuation
ValueCountFrequency (%)
) 37
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3889
91.7%
Common 350
 
8.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
k 909
23.4%
O 872
22.4%
s 364
9.4%
e 293
 
7.5%
o 202
 
5.2%
l 128
 
3.3%
u 128
 
3.3%
b 128
 
3.3%
n 111
 
2.9%
a 111
 
2.9%
Other values (10) 643
16.5%
Common
ValueCountFrequency (%)
276
78.9%
( 37
 
10.6%
) 37
 
10.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4239
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
k 909
21.4%
O 872
20.6%
s 364
8.6%
e 293
 
6.9%
276
 
6.5%
o 202
 
4.8%
l 128
 
3.0%
u 128
 
3.0%
b 128
 
3.0%
n 111
 
2.6%
Other values (13) 828
19.5%
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size58.9 KiB
2023-12-09T23:29:50.155436image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length33
Median length2
Mean length3.159
Min length2

Characters and Unicode

Total characters3159
Distinct characters23
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st rowOk
2nd rowOk
3rd rowOk
4th rowOk
5th rowOk
ValueCountFrequency (%)
ok 962
81.1%
unable 37
 
3.1%
to 37
 
3.1%
check 37
 
3.1%
not 37
 
3.1%
enough 37
 
3.1%
data 37
 
3.1%
possible 1
 
0.1%
issue 1
 
0.1%
2023-12-09T23:29:50.414609image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
k 999
31.6%
O 962
30.5%
186
 
5.9%
e 113
 
3.6%
o 112
 
3.5%
n 111
 
3.5%
a 111
 
3.5%
t 111
 
3.5%
h 74
 
2.3%
u 38
 
1.2%
Other values (13) 342
 
10.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1861
58.9%
Uppercase Letter 1038
32.9%
Space Separator 186
 
5.9%
Close Punctuation 37
 
1.2%
Open Punctuation 37
 
1.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
k 999
53.7%
e 113
 
6.1%
o 112
 
6.0%
n 111
 
6.0%
a 111
 
6.0%
t 111
 
6.0%
h 74
 
4.0%
u 38
 
2.0%
b 38
 
2.0%
l 38
 
2.0%
Other values (5) 116
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
O 962
92.7%
C 37
 
3.6%
U 37
 
3.6%
P 1
 
0.1%
I 1
 
0.1%
Space Separator
ValueCountFrequency (%)
186
100.0%
Close Punctuation
ValueCountFrequency (%)
) 37
100.0%
Open Punctuation
ValueCountFrequency (%)
( 37
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2899
91.8%
Common 260
 
8.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
k 999
34.5%
O 962
33.2%
e 113
 
3.9%
o 112
 
3.9%
n 111
 
3.8%
a 111
 
3.8%
t 111
 
3.8%
h 74
 
2.6%
u 38
 
1.3%
b 38
 
1.3%
Other values (10) 230
 
7.9%
Common
ValueCountFrequency (%)
186
71.5%
) 37
 
14.2%
( 37
 
14.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3159
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
k 999
31.6%
O 962
30.5%
186
 
5.9%
e 113
 
3.6%
o 112
 
3.5%
n 111
 
3.5%
a 111
 
3.5%
t 111
 
3.5%
h 74
 
2.3%
u 38
 
1.2%
Other values (13) 342
 
10.8%
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size58.9 KiB
2023-12-09T23:29:50.555335image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length33
Median length2
Mean length3.159
Min length2

Characters and Unicode

Total characters3159
Distinct characters23
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st rowOk
2nd rowOk
3rd rowOk
4th rowOk
5th rowOk
ValueCountFrequency (%)
ok 962
81.1%
unable 37
 
3.1%
to 37
 
3.1%
check 37
 
3.1%
not 37
 
3.1%
enough 37
 
3.1%
data 37
 
3.1%
possible 1
 
0.1%
issue 1
 
0.1%
2023-12-09T23:29:50.810004image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
k 999
31.6%
O 962
30.5%
186
 
5.9%
e 113
 
3.6%
o 112
 
3.5%
n 111
 
3.5%
a 111
 
3.5%
t 111
 
3.5%
h 74
 
2.3%
u 38
 
1.2%
Other values (13) 342
 
10.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1861
58.9%
Uppercase Letter 1038
32.9%
Space Separator 186
 
5.9%
Close Punctuation 37
 
1.2%
Open Punctuation 37
 
1.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
k 999
53.7%
e 113
 
6.1%
o 112
 
6.0%
n 111
 
6.0%
a 111
 
6.0%
t 111
 
6.0%
h 74
 
4.0%
u 38
 
2.0%
b 38
 
2.0%
l 38
 
2.0%
Other values (5) 116
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
O 962
92.7%
C 37
 
3.6%
U 37
 
3.6%
P 1
 
0.1%
I 1
 
0.1%
Space Separator
ValueCountFrequency (%)
186
100.0%
Close Punctuation
ValueCountFrequency (%)
) 37
100.0%
Open Punctuation
ValueCountFrequency (%)
( 37
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2899
91.8%
Common 260
 
8.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
k 999
34.5%
O 962
33.2%
e 113
 
3.9%
o 112
 
3.9%
n 111
 
3.8%
a 111
 
3.8%
t 111
 
3.8%
h 74
 
2.6%
u 38
 
1.3%
b 38
 
1.3%
Other values (10) 230
 
7.9%
Common
ValueCountFrequency (%)
186
71.5%
) 37
 
14.2%
( 37
 
14.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3159
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
k 999
31.6%
O 962
30.5%
186
 
5.9%
e 113
 
3.6%
o 112
 
3.5%
n 111
 
3.5%
a 111
 
3.5%
t 111
 
3.5%
h 74
 
2.3%
u 38
 
1.2%
Other values (13) 342
 
10.8%
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size59.5 KiB
2023-12-09T23:29:50.954571image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length33
Median length2
Mean length3.783
Min length2

Characters and Unicode

Total characters3783
Distinct characters23
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowOk
2nd rowOk
3rd rowOk
4th rowOk
5th rowOk
ValueCountFrequency (%)
ok 910
73.5%
possible 53
 
4.3%
issue 53
 
4.3%
unable 37
 
3.0%
to 37
 
3.0%
check 37
 
3.0%
not 37
 
3.0%
enough 37
 
3.0%
data 37
 
3.0%
2023-12-09T23:29:51.212327image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
k 947
25.0%
O 910
24.1%
238
 
6.3%
e 217
 
5.7%
s 212
 
5.6%
o 164
 
4.3%
t 111
 
2.9%
a 111
 
2.9%
n 111
 
2.9%
u 90
 
2.4%
Other values (13) 672
17.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2381
62.9%
Uppercase Letter 1090
28.8%
Space Separator 238
 
6.3%
Open Punctuation 37
 
1.0%
Close Punctuation 37
 
1.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
k 947
39.8%
e 217
 
9.1%
s 212
 
8.9%
o 164
 
6.9%
t 111
 
4.7%
a 111
 
4.7%
n 111
 
4.7%
u 90
 
3.8%
l 90
 
3.8%
b 90
 
3.8%
Other values (5) 238
 
10.0%
Uppercase Letter
ValueCountFrequency (%)
O 910
83.5%
I 53
 
4.9%
P 53
 
4.9%
U 37
 
3.4%
C 37
 
3.4%
Space Separator
ValueCountFrequency (%)
238
100.0%
Open Punctuation
ValueCountFrequency (%)
( 37
100.0%
Close Punctuation
ValueCountFrequency (%)
) 37
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3471
91.8%
Common 312
 
8.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
k 947
27.3%
O 910
26.2%
e 217
 
6.3%
s 212
 
6.1%
o 164
 
4.7%
t 111
 
3.2%
a 111
 
3.2%
n 111
 
3.2%
u 90
 
2.6%
l 90
 
2.6%
Other values (10) 508
14.6%
Common
ValueCountFrequency (%)
238
76.3%
( 37
 
11.9%
) 37
 
11.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3783
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
k 947
25.0%
O 910
24.1%
238
 
6.3%
e 217
 
5.7%
s 212
 
5.6%
o 164
 
4.3%
t 111
 
2.9%
a 111
 
2.9%
n 111
 
2.9%
u 90
 
2.4%
Other values (13) 672
17.8%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size57.8 KiB
2023-12-09T23:29:51.349236image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length14
Median length2
Mean length2.036
Min length2

Characters and Unicode

Total characters2036
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowOk
2nd rowOk
3rd rowOk
4th rowOk
5th rowOk
ValueCountFrequency (%)
ok 997
99.4%
possible 3
 
0.3%
issue 3
 
0.3%
2023-12-09T23:29:51.608748image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
O 997
49.0%
k 997
49.0%
s 12
 
0.6%
e 6
 
0.3%
P 3
 
0.1%
o 3
 
0.1%
i 3
 
0.1%
b 3
 
0.1%
l 3
 
0.1%
3
 
0.1%
Other values (2) 6
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1030
50.6%
Uppercase Letter 1003
49.3%
Space Separator 3
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
k 997
96.8%
s 12
 
1.2%
e 6
 
0.6%
o 3
 
0.3%
i 3
 
0.3%
b 3
 
0.3%
l 3
 
0.3%
u 3
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
O 997
99.4%
P 3
 
0.3%
I 3
 
0.3%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2033
99.9%
Common 3
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
O 997
49.0%
k 997
49.0%
s 12
 
0.6%
e 6
 
0.3%
P 3
 
0.1%
o 3
 
0.1%
i 3
 
0.1%
b 3
 
0.1%
l 3
 
0.1%
I 3
 
0.1%
Common
ValueCountFrequency (%)
3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2036
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
O 997
49.0%
k 997
49.0%
s 12
 
0.6%
e 6
 
0.3%
P 3
 
0.1%
o 3
 
0.1%
i 3
 
0.1%
b 3
 
0.1%
l 3
 
0.1%
3
 
0.1%
Other values (2) 6
 
0.3%
Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size57.7 KiB
2023-12-09T23:29:51.720670image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2000
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowOk
2nd rowOk
3rd rowOk
4th rowOk
5th rowOk
ValueCountFrequency (%)
ok 1000
100.0%
2023-12-09T23:29:51.960341image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
O 1000
50.0%
k 1000
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1000
50.0%
Lowercase Letter 1000
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
O 1000
100.0%
Lowercase Letter
ValueCountFrequency (%)
k 1000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2000
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
O 1000
50.0%
k 1000
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
O 1000
50.0%
k 1000
50.0%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size58.2 KiB
2023-12-09T23:29:52.109986image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.472
Min length2

Characters and Unicode

Total characters2472
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 528
52.8%
yes 472
47.2%
2023-12-09T23:29:52.371052image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 528
21.4%
o 528
21.4%
Y 472
19.1%
e 472
19.1%
s 472
19.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1472
59.5%
Uppercase Letter 1000
40.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 528
35.9%
e 472
32.1%
s 472
32.1%
Uppercase Letter
ValueCountFrequency (%)
N 528
52.8%
Y 472
47.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 2472
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 528
21.4%
o 528
21.4%
Y 472
19.1%
e 472
19.1%
s 472
19.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2472
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 528
21.4%
o 528
21.4%
Y 472
19.1%
e 472
19.1%
s 472
19.1%
Distinct47
Distinct (%)10.0%
Missing528
Missing (%)52.8%
Memory size53.5 KiB
2023-12-09T23:29:52.636227image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length23
Median length23
Mean length23
Min length23

Characters and Unicode

Total characters10856
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)2.5%

Sample

1st row2018-02-13T00:00:00.000
2nd row2018-02-06T00:00:00.000
3rd row2018-02-15T00:00:00.000
4th row2018-02-15T00:00:00.000
5th row2018-02-16T00:00:00.000
ValueCountFrequency (%)
2018-04-03t00:00:00.000 57
 
12.1%
2018-04-04t00:00:00.000 52
 
11.0%
2018-03-29t00:00:00.000 28
 
5.9%
2018-03-12t00:00:00.000 23
 
4.9%
2018-03-26t00:00:00.000 21
 
4.4%
2018-03-14t00:00:00.000 19
 
4.0%
2018-03-23t00:00:00.000 19
 
4.0%
2018-03-05t00:00:00.000 18
 
3.8%
2018-03-19t00:00:00.000 18
 
3.8%
2018-03-16t00:00:00.000 18
 
3.8%
Other values (37) 199
42.2%
2023-12-09T23:29:53.022034image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5406
49.8%
- 944
 
8.7%
: 944
 
8.7%
2 748
 
6.9%
1 603
 
5.6%
8 494
 
4.6%
T 472
 
4.3%
. 472
 
4.3%
3 379
 
3.5%
4 207
 
1.9%
Other values (4) 187
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8024
73.9%
Other Punctuation 1416
 
13.0%
Dash Punctuation 944
 
8.7%
Uppercase Letter 472
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5406
67.4%
2 748
 
9.3%
1 603
 
7.5%
8 494
 
6.2%
3 379
 
4.7%
4 207
 
2.6%
9 65
 
0.8%
6 63
 
0.8%
5 44
 
0.5%
7 15
 
0.2%
Other Punctuation
ValueCountFrequency (%)
: 944
66.7%
. 472
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 944
100.0%
Uppercase Letter
ValueCountFrequency (%)
T 472
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10384
95.7%
Latin 472
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5406
52.1%
- 944
 
9.1%
: 944
 
9.1%
2 748
 
7.2%
1 603
 
5.8%
8 494
 
4.8%
. 472
 
4.5%
3 379
 
3.6%
4 207
 
2.0%
9 65
 
0.6%
Other values (3) 122
 
1.2%
Latin
ValueCountFrequency (%)
T 472
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10856
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5406
49.8%
- 944
 
8.7%
: 944
 
8.7%
2 748
 
6.9%
1 603
 
5.6%
8 494
 
4.6%
T 472
 
4.3%
. 472
 
4.3%
3 379
 
3.5%
4 207
 
1.9%
Other values (4) 187
 
1.7%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size58.1 KiB
2023-12-09T23:29:53.163883image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.329
Min length2

Characters and Unicode

Total characters2329
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowYes
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 671
67.1%
yes 329
32.9%
2023-12-09T23:29:53.418549image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 671
28.8%
o 671
28.8%
Y 329
14.1%
e 329
14.1%
s 329
14.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1329
57.1%
Uppercase Letter 1000
42.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 671
50.5%
e 329
24.8%
s 329
24.8%
Uppercase Letter
ValueCountFrequency (%)
N 671
67.1%
Y 329
32.9%

Most occurring scripts

ValueCountFrequency (%)
Latin 2329
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 671
28.8%
o 671
28.8%
Y 329
14.1%
e 329
14.1%
s 329
14.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2329
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 671
28.8%
o 671
28.8%
Y 329
14.1%
e 329
14.1%
s 329
14.1%
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size58.9 KiB
2023-12-09T23:29:53.556436image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length33
Median length2
Mean length3.219
Min length2

Characters and Unicode

Total characters3219
Distinct characters21
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 891
75.2%
yes 72
 
6.1%
unable 37
 
3.1%
to 37
 
3.1%
check 37
 
3.1%
not 37
 
3.1%
enough 37
 
3.1%
data 37
 
3.1%
2023-12-09T23:29:53.816949image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 1002
31.1%
N 891
27.7%
185
 
5.7%
e 183
 
5.7%
n 111
 
3.4%
a 111
 
3.4%
t 111
 
3.4%
h 74
 
2.3%
Y 72
 
2.2%
s 72
 
2.2%
Other values (11) 407
12.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1923
59.7%
Uppercase Letter 1037
32.2%
Space Separator 185
 
5.7%
Open Punctuation 37
 
1.1%
Close Punctuation 37
 
1.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 1002
52.1%
e 183
 
9.5%
n 111
 
5.8%
a 111
 
5.8%
t 111
 
5.8%
h 74
 
3.8%
s 72
 
3.7%
k 37
 
1.9%
d 37
 
1.9%
g 37
 
1.9%
Other values (4) 148
 
7.7%
Uppercase Letter
ValueCountFrequency (%)
N 891
85.9%
Y 72
 
6.9%
C 37
 
3.6%
U 37
 
3.6%
Space Separator
ValueCountFrequency (%)
185
100.0%
Open Punctuation
ValueCountFrequency (%)
( 37
100.0%
Close Punctuation
ValueCountFrequency (%)
) 37
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2960
92.0%
Common 259
 
8.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 1002
33.9%
N 891
30.1%
e 183
 
6.2%
n 111
 
3.8%
a 111
 
3.8%
t 111
 
3.8%
h 74
 
2.5%
Y 72
 
2.4%
s 72
 
2.4%
k 37
 
1.2%
Other values (8) 296
 
10.0%
Common
ValueCountFrequency (%)
185
71.4%
( 37
 
14.3%
) 37
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3219
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 1002
31.1%
N 891
27.7%
185
 
5.7%
e 183
 
5.7%
n 111
 
3.4%
a 111
 
3.4%
t 111
 
3.4%
h 74
 
2.3%
Y 72
 
2.2%
s 72
 
2.2%
Other values (11) 407
12.6%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size57.8 KiB
2023-12-09T23:29:53.934420image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.04
Min length2

Characters and Unicode

Total characters2040
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 960
96.0%
yes 40
 
4.0%
2023-12-09T23:29:54.163790image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 960
47.1%
o 960
47.1%
Y 40
 
2.0%
e 40
 
2.0%
s 40
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1040
51.0%
Uppercase Letter 1000
49.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 960
92.3%
e 40
 
3.8%
s 40
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
N 960
96.0%
Y 40
 
4.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2040
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 960
47.1%
o 960
47.1%
Y 40
 
2.0%
e 40
 
2.0%
s 40
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2040
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 960
47.1%
o 960
47.1%
Y 40
 
2.0%
e 40
 
2.0%
s 40
 
2.0%
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size63.1 KiB
2023-12-09T23:29:54.317653image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length33
Median length2
Mean length7.488
Min length2

Characters and Unicode

Total characters7488
Distinct characters21
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowYes
ValueCountFrequency (%)
no 792
42.1%
unable 176
 
9.4%
to 176
 
9.4%
check 176
 
9.4%
not 176
 
9.4%
enough 176
 
9.4%
data 176
 
9.4%
yes 32
 
1.7%
2023-12-09T23:29:54.583436image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 1320
17.6%
880
11.8%
N 792
10.6%
e 560
 
7.5%
n 528
 
7.1%
a 528
 
7.1%
t 528
 
7.1%
h 352
 
4.7%
( 176
 
2.4%
) 176
 
2.4%
Other values (11) 1648
22.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5080
67.8%
Uppercase Letter 1176
 
15.7%
Space Separator 880
 
11.8%
Open Punctuation 176
 
2.4%
Close Punctuation 176
 
2.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 1320
26.0%
e 560
11.0%
n 528
 
10.4%
a 528
 
10.4%
t 528
 
10.4%
h 352
 
6.9%
d 176
 
3.5%
g 176
 
3.5%
u 176
 
3.5%
k 176
 
3.5%
Other values (4) 560
11.0%
Uppercase Letter
ValueCountFrequency (%)
N 792
67.3%
C 176
 
15.0%
U 176
 
15.0%
Y 32
 
2.7%
Space Separator
ValueCountFrequency (%)
880
100.0%
Open Punctuation
ValueCountFrequency (%)
( 176
100.0%
Close Punctuation
ValueCountFrequency (%)
) 176
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6256
83.5%
Common 1232
 
16.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 1320
21.1%
N 792
12.7%
e 560
9.0%
n 528
 
8.4%
a 528
 
8.4%
t 528
 
8.4%
h 352
 
5.6%
d 176
 
2.8%
g 176
 
2.8%
u 176
 
2.8%
Other values (8) 1120
17.9%
Common
ValueCountFrequency (%)
880
71.4%
( 176
 
14.3%
) 176
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7488
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 1320
17.6%
880
11.8%
N 792
10.6%
e 560
 
7.5%
n 528
 
7.1%
a 528
 
7.1%
t 528
 
7.1%
h 352
 
4.7%
( 176
 
2.4%
) 176
 
2.4%
Other values (11) 1648
22.0%
Distinct786
Distinct (%)78.6%
Missing0
Missing (%)0.0%
Memory size61.1 KiB
2023-12-09T23:29:54.968812image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.444
Min length5

Characters and Unicode

Total characters5444
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique658 ?
Unique (%)65.8%

Sample

1st row169416
2nd row104407
3rd row94380
4th row125000
5th row50000
ValueCountFrequency (%)
60000 11
 
1.1%
50000 9
 
0.9%
80000 8
 
0.8%
57000 8
 
0.8%
280358 6
 
0.6%
63000 6
 
0.6%
200000 5
 
0.5%
65968 5
 
0.5%
100000 5
 
0.5%
88000 4
 
0.4%
Other values (776) 933
93.3%
2023-12-09T23:29:55.504287image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1434
26.3%
1 554
 
10.2%
5 528
 
9.7%
6 465
 
8.5%
2 464
 
8.5%
8 436
 
8.0%
7 414
 
7.6%
3 408
 
7.5%
4 406
 
7.5%
9 335
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5444
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1434
26.3%
1 554
 
10.2%
5 528
 
9.7%
6 465
 
8.5%
2 464
 
8.5%
8 436
 
8.0%
7 414
 
7.6%
3 408
 
7.5%
4 406
 
7.5%
9 335
 
6.2%

Most occurring scripts

ValueCountFrequency (%)
Common 5444
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1434
26.3%
1 554
 
10.2%
5 528
 
9.7%
6 465
 
8.5%
2 464
 
8.5%
8 436
 
8.0%
7 414
 
7.6%
3 408
 
7.5%
4 406
 
7.5%
9 335
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5444
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1434
26.3%
1 554
 
10.2%
5 528
 
9.7%
6 465
 
8.5%
2 464
 
8.5%
8 436
 
8.0%
7 414
 
7.6%
3 408
 
7.5%
4 406
 
7.5%
9 335
 
6.2%
Distinct788
Distinct (%)78.8%
Missing0
Missing (%)0.0%
Memory size61.1 KiB
2023-12-09T23:29:55.914688image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length8
Median length5
Mean length5.459
Min length4

Characters and Unicode

Total characters5459
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique660 ?
Unique (%)66.0%

Sample

1st row169416
2nd row104407
3rd row94380
4th row125000
5th row50000
ValueCountFrequency (%)
60000 11
 
1.1%
50000 9
 
0.9%
57000 8
 
0.8%
80000 7
 
0.7%
63000 6
 
0.6%
160000 6
 
0.6%
280358 6
 
0.6%
200000 5
 
0.5%
75000 5
 
0.5%
123968 5
 
0.5%
Other values (778) 932
93.2%
2023-12-09T23:29:56.458629image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1420
26.0%
1 557
 
10.2%
5 527
 
9.7%
6 477
 
8.7%
2 476
 
8.7%
8 433
 
7.9%
3 421
 
7.7%
7 415
 
7.6%
4 394
 
7.2%
9 337
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5457
> 99.9%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1420
26.0%
1 557
 
10.2%
5 527
 
9.7%
6 477
 
8.7%
2 476
 
8.7%
8 433
 
7.9%
3 421
 
7.7%
7 415
 
7.6%
4 394
 
7.2%
9 337
 
6.2%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5459
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1420
26.0%
1 557
 
10.2%
5 527
 
9.7%
6 477
 
8.7%
2 476
 
8.7%
8 433
 
7.9%
3 421
 
7.7%
7 415
 
7.6%
4 394
 
7.2%
9 337
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5459
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1420
26.0%
1 557
 
10.2%
5 527
 
9.7%
6 477
 
8.7%
2 476
 
8.7%
8 433
 
7.9%
3 421
 
7.7%
7 415
 
7.6%
4 394
 
7.2%
9 337
 
6.2%
Distinct788
Distinct (%)78.8%
Missing0
Missing (%)0.0%
Memory size61.1 KiB
2023-12-09T23:29:56.864107image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length8
Median length5
Mean length5.449
Min length4

Characters and Unicode

Total characters5449
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique661 ?
Unique (%)66.1%

Sample

1st row169416
2nd row104407
3rd row94380
4th row125000
5th row50000
ValueCountFrequency (%)
60000 11
 
1.1%
50000 9
 
0.9%
57000 8
 
0.8%
80000 7
 
0.7%
280358 6
 
0.6%
63000 6
 
0.6%
200000 5
 
0.5%
65968 5
 
0.5%
150000 5
 
0.5%
35000 4
 
0.4%
Other values (778) 934
93.4%
2023-12-09T23:29:57.399508image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1438
26.4%
1 558
 
10.2%
5 532
 
9.8%
6 469
 
8.6%
2 468
 
8.6%
8 435
 
8.0%
3 411
 
7.5%
7 410
 
7.5%
4 398
 
7.3%
9 328
 
6.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5447
> 99.9%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1438
26.4%
1 558
 
10.2%
5 532
 
9.8%
6 469
 
8.6%
2 468
 
8.6%
8 435
 
8.0%
3 411
 
7.5%
7 410
 
7.5%
4 398
 
7.3%
9 328
 
6.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5449
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1438
26.4%
1 558
 
10.2%
5 532
 
9.8%
6 469
 
8.6%
2 468
 
8.6%
8 435
 
8.0%
3 411
 
7.5%
7 410
 
7.5%
4 398
 
7.3%
9 328
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5449
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1438
26.4%
1 558
 
10.2%
5 532
 
9.8%
6 469
 
8.6%
2 468
 
8.6%
8 435
 
8.0%
3 411
 
7.5%
7 410
 
7.5%
4 398
 
7.3%
9 328
 
6.0%
Distinct51
Distinct (%)77.3%
Missing934
Missing (%)93.4%
Memory size33.3 KiB
2023-12-09T23:29:57.674702image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.757575758
Min length1

Characters and Unicode

Total characters314
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)65.2%

Sample

1st row65226
2nd row73500
3rd row10000
4th row20000
5th row10000
ValueCountFrequency (%)
58000 5
 
7.6%
10000 4
 
6.1%
0 3
 
4.5%
20000 3
 
4.5%
90723 2
 
3.0%
2000 2
 
3.0%
101887 2
 
3.0%
31625 2
 
3.0%
847154 1
 
1.5%
25000 1
 
1.5%
Other values (41) 41
62.1%
2023-12-09T23:29:58.066982image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 101
32.2%
1 30
 
9.6%
2 29
 
9.2%
5 28
 
8.9%
8 25
 
8.0%
7 25
 
8.0%
3 23
 
7.3%
6 22
 
7.0%
9 18
 
5.7%
4 13
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 314
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 101
32.2%
1 30
 
9.6%
2 29
 
9.2%
5 28
 
8.9%
8 25
 
8.0%
7 25
 
8.0%
3 23
 
7.3%
6 22
 
7.0%
9 18
 
5.7%
4 13
 
4.1%

Most occurring scripts

ValueCountFrequency (%)
Common 314
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 101
32.2%
1 30
 
9.6%
2 29
 
9.2%
5 28
 
8.9%
8 25
 
8.0%
7 25
 
8.0%
3 23
 
7.3%
6 22
 
7.0%
9 18
 
5.7%
4 13
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 314
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 101
32.2%
1 30
 
9.6%
2 29
 
9.2%
5 28
 
8.9%
8 25
 
8.0%
7 25
 
8.0%
3 23
 
7.3%
6 22
 
7.0%
9 18
 
5.7%
4 13
 
4.1%

water_current_date
Text

MISSING 

Distinct25
Distinct (%)3.2%
Missing210
Missing (%)21.0%
Memory size68.4 KiB
2023-12-09T23:29:58.293993image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length23
Median length23
Mean length23
Min length23

Characters and Unicode

Total characters18170
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)0.8%

Sample

1st row2017-12-31T00:00:00.000
2nd row2018-12-31T00:00:00.000
3rd row2017-12-31T00:00:00.000
4th row2017-12-31T00:00:00.000
5th row2018-02-28T00:00:00.000
ValueCountFrequency (%)
2017-12-31t00:00:00.000 568
71.9%
2016-12-31t00:00:00.000 64
 
8.1%
2018-01-31t00:00:00.000 44
 
5.6%
2018-02-28t00:00:00.000 22
 
2.8%
2015-12-31t00:00:00.000 18
 
2.3%
2016-02-29t00:00:00.000 9
 
1.1%
2012-12-31t00:00:00.000 8
 
1.0%
2017-02-28t00:00:00.000 7
 
0.9%
2013-12-31t00:00:00.000 7
 
0.9%
2017-11-30t00:00:00.000 6
 
0.8%
Other values (15) 37
 
4.7%
2023-12-09T23:29:58.618240image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 8021
44.1%
1 2274
 
12.5%
- 1580
 
8.7%
: 1580
 
8.7%
2 1548
 
8.5%
T 790
 
4.3%
. 790
 
4.3%
3 764
 
4.2%
7 602
 
3.3%
8 106
 
0.6%
Other values (4) 115
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13430
73.9%
Other Punctuation 2370
 
13.0%
Dash Punctuation 1580
 
8.7%
Uppercase Letter 790
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 8021
59.7%
1 2274
 
16.9%
2 1548
 
11.5%
3 764
 
5.7%
7 602
 
4.5%
8 106
 
0.8%
6 81
 
0.6%
5 19
 
0.1%
9 9
 
0.1%
4 6
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
: 1580
66.7%
. 790
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 1580
100.0%
Uppercase Letter
ValueCountFrequency (%)
T 790
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 17380
95.7%
Latin 790
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 8021
46.2%
1 2274
 
13.1%
- 1580
 
9.1%
: 1580
 
9.1%
2 1548
 
8.9%
. 790
 
4.5%
3 764
 
4.4%
7 602
 
3.5%
8 106
 
0.6%
6 81
 
0.5%
Other values (3) 34
 
0.2%
Latin
ValueCountFrequency (%)
T 790
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18170
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 8021
44.1%
1 2274
 
12.5%
- 1580
 
8.7%
: 1580
 
8.7%
2 1548
 
8.5%
T 790
 
4.3%
. 790
 
4.3%
3 764
 
4.2%
7 602
 
3.3%
8 106
 
0.6%
Other values (4) 115
 
0.6%
Distinct542
Distinct (%)84.7%
Missing360
Missing (%)36.0%
Memory size50.5 KiB
2023-12-09T23:29:59.035457image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length9
Median length6
Mean length5.61875
Min length1

Characters and Unicode

Total characters3596
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique464 ?
Unique (%)72.5%

Sample

1st row3635.5
2nd row116
3rd row102.9
4th row10762.6
5th row790.1
ValueCountFrequency (%)
0 7
 
1.1%
2553.9 5
 
0.8%
463 5
 
0.8%
1227.4 4
 
0.6%
45.5 3
 
0.5%
29 3
 
0.5%
15989.4 3
 
0.5%
57.2 3
 
0.5%
3016.1 3
 
0.5%
293.2 3
 
0.5%
Other values (532) 601
93.9%
2023-12-09T23:29:59.617297image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 540
15.0%
1 409
11.4%
2 384
10.7%
3 332
9.2%
4 320
8.9%
5 302
8.4%
7 292
8.1%
8 270
7.5%
6 268
7.5%
9 257
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3056
85.0%
Other Punctuation 540
 
15.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 409
13.4%
2 384
12.6%
3 332
10.9%
4 320
10.5%
5 302
9.9%
7 292
9.6%
8 270
8.8%
6 268
8.8%
9 257
8.4%
0 222
7.3%
Other Punctuation
ValueCountFrequency (%)
. 540
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3596
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 540
15.0%
1 409
11.4%
2 384
10.7%
3 332
9.2%
4 320
8.9%
5 302
8.4%
7 292
8.1%
8 270
7.5%
6 268
7.5%
9 257
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3596
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 540
15.0%
1 409
11.4%
2 384
10.7%
3 332
9.2%
4 320
8.9%
5 302
8.4%
7 292
8.1%
8 270
7.5%
6 268
7.5%
9 257
7.1%
Distinct496
Distinct (%)84.6%
Missing414
Missing (%)41.4%
Memory size48.9 KiB
2023-12-09T23:30:00.029815image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length9
Median length6
Mean length5.583617747
Min length1

Characters and Unicode

Total characters3272
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique426 ?
Unique (%)72.7%

Sample

1st row116
2nd row102.9
3rd row10762.6
4th row790.1
5th row143
ValueCountFrequency (%)
0 7
 
1.2%
2553.9 5
 
0.9%
463 5
 
0.9%
1227.4 4
 
0.7%
15989.4 3
 
0.5%
57.2 3
 
0.5%
1224.6 3
 
0.5%
29 3
 
0.5%
887.2 3
 
0.5%
3016.1 3
 
0.5%
Other values (486) 547
93.3%
2023-12-09T23:30:00.597390image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 490
15.0%
1 374
11.4%
2 355
10.8%
3 305
9.3%
4 277
8.5%
5 275
8.4%
7 256
7.8%
8 249
7.6%
9 246
7.5%
6 244
7.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2782
85.0%
Other Punctuation 490
 
15.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 374
13.4%
2 355
12.8%
3 305
11.0%
4 277
10.0%
5 275
9.9%
7 256
9.2%
8 249
9.0%
9 246
8.8%
6 244
8.8%
0 201
7.2%
Other Punctuation
ValueCountFrequency (%)
. 490
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3272
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 490
15.0%
1 374
11.4%
2 355
10.8%
3 305
9.3%
4 277
8.5%
5 275
8.4%
7 256
7.8%
8 249
7.6%
9 246
7.5%
6 244
7.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3272
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 490
15.0%
1 374
11.4%
2 355
10.8%
3 305
9.3%
4 277
8.5%
5 275
8.4%
7 256
7.8%
8 249
7.6%
9 246
7.5%
6 244
7.5%
Distinct488
Distinct (%)83.3%
Missing414
Missing (%)41.4%
Memory size48.5 KiB
2023-12-09T23:30:01.075406image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length8
Median length5
Mean length4.846416382
Min length1

Characters and Unicode

Total characters2840
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique411 ?
Unique (%)70.1%

Sample

1st row1.11
2nd row1.09
3rd row86.1
4th row15.8
5th row2.86
ValueCountFrequency (%)
0 8
 
1.4%
7.02 5
 
0.9%
10.21 4
 
0.7%
0.91 4
 
0.7%
25.54 3
 
0.5%
22.18 3
 
0.5%
0.68 3
 
0.5%
13.8 3
 
0.5%
6.08 3
 
0.5%
13.51 3
 
0.5%
Other values (478) 547
93.3%
2023-12-09T23:30:01.692832image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 573
20.2%
1 344
12.1%
2 254
8.9%
3 237
8.3%
4 231
8.1%
6 215
 
7.6%
5 214
 
7.5%
9 208
 
7.3%
8 197
 
6.9%
7 195
 
6.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2267
79.8%
Other Punctuation 573
 
20.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 344
15.2%
2 254
11.2%
3 237
10.5%
4 231
10.2%
6 215
9.5%
5 214
9.4%
9 208
9.2%
8 197
8.7%
7 195
8.6%
0 172
7.6%
Other Punctuation
ValueCountFrequency (%)
. 573
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2840
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 573
20.2%
1 344
12.1%
2 254
8.9%
3 237
8.3%
4 231
8.1%
6 215
 
7.6%
5 214
 
7.5%
9 208
 
7.3%
8 197
 
6.9%
7 195
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2840
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 573
20.2%
1 344
12.1%
2 254
8.9%
3 237
8.3%
4 231
8.1%
6 215
 
7.6%
5 214
 
7.5%
9 208
 
7.3%
8 197
 
6.9%
7 195
 
6.9%
Distinct4
Distinct (%)100.0%
Missing996
Missing (%)99.6%
Memory size31.5 KiB
2023-12-09T23:30:01.889573image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length5.5
Mean length5.5
Min length5

Characters and Unicode

Total characters22
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st row1003.2
2nd row521.6
3rd row404.3
4th row2492.9
ValueCountFrequency (%)
404.3 1
25.0%
1003.2 1
25.0%
2492.9 1
25.0%
521.6 1
25.0%
2023-12-09T23:30:02.188608image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 4
18.2%
2 4
18.2%
4 3
13.6%
0 3
13.6%
3 2
9.1%
1 2
9.1%
9 2
9.1%
5 1
 
4.5%
6 1
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 18
81.8%
Other Punctuation 4
 
18.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 4
22.2%
4 3
16.7%
0 3
16.7%
3 2
11.1%
1 2
11.1%
9 2
11.1%
5 1
 
5.6%
6 1
 
5.6%
Other Punctuation
ValueCountFrequency (%)
. 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 22
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 4
18.2%
2 4
18.2%
4 3
13.6%
0 3
13.6%
3 2
9.1%
1 2
9.1%
9 2
9.1%
5 1
 
4.5%
6 1
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 4
18.2%
2 4
18.2%
4 3
13.6%
0 3
13.6%
3 2
9.1%
1 2
9.1%
9 2
9.1%
5 1
 
4.5%
6 1
 
4.5%
Distinct52
Distinct (%)85.2%
Missing939
Missing (%)93.9%
Memory size33.2 KiB
2023-12-09T23:30:02.469753image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.754098361
Min length1

Characters and Unicode

Total characters351
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)70.5%

Sample

1st row3635.5
2nd row1380
3rd row20741.2
4th row4800
5th row77.7
ValueCountFrequency (%)
17666.2 2
 
3.3%
1444.8 2
 
3.3%
16423.7 2
 
3.3%
538 2
 
3.3%
2022.1 2
 
3.3%
2179.8 2
 
3.3%
1914.4 2
 
3.3%
2563.2 2
 
3.3%
77.7 2
 
3.3%
7505.3 1
 
1.6%
Other values (42) 42
68.9%
2023-12-09T23:30:02.878127image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 54
15.4%
1 42
12.0%
2 42
12.0%
4 38
10.8%
7 35
10.0%
5 31
8.8%
6 27
7.7%
3 27
7.7%
0 22
6.3%
8 17
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 297
84.6%
Other Punctuation 54
 
15.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 42
14.1%
2 42
14.1%
4 38
12.8%
7 35
11.8%
5 31
10.4%
6 27
9.1%
3 27
9.1%
0 22
7.4%
8 17
5.7%
9 16
 
5.4%
Other Punctuation
ValueCountFrequency (%)
. 54
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 351
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 54
15.4%
1 42
12.0%
2 42
12.0%
4 38
10.8%
7 35
10.0%
5 31
8.8%
6 27
7.7%
3 27
7.7%
0 22
6.3%
8 17
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 351
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 54
15.4%
1 42
12.0%
2 42
12.0%
4 38
10.8%
7 35
10.0%
5 31
8.8%
6 27
7.7%
3 27
7.7%
0 22
6.3%
8 17
 
4.8%
Distinct496
Distinct (%)84.6%
Missing414
Missing (%)41.4%
Memory size48.9 KiB
2023-12-09T23:30:03.297015image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length9
Median length6
Mean length5.583617747
Min length1

Characters and Unicode

Total characters3272
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique426 ?
Unique (%)72.7%

Sample

1st row116
2nd row102.9
3rd row10762.6
4th row790.1
5th row143
ValueCountFrequency (%)
0 7
 
1.2%
2553.9 5
 
0.9%
463 5
 
0.9%
1227.4 4
 
0.7%
15989.4 3
 
0.5%
57.2 3
 
0.5%
1224.6 3
 
0.5%
29 3
 
0.5%
887.2 3
 
0.5%
3016.1 3
 
0.5%
Other values (486) 547
93.3%
2023-12-09T23:30:03.862692image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 490
15.0%
1 374
11.4%
2 355
10.8%
3 305
9.3%
4 277
8.5%
5 275
8.4%
7 256
7.8%
8 249
7.6%
9 246
7.5%
6 244
7.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2782
85.0%
Other Punctuation 490
 
15.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 374
13.4%
2 355
12.8%
3 305
11.0%
4 277
10.0%
5 275
9.9%
7 256
9.2%
8 249
9.0%
9 246
8.8%
6 244
8.8%
0 201
7.2%
Other Punctuation
ValueCountFrequency (%)
. 490
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3272
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 490
15.0%
1 374
11.4%
2 355
10.8%
3 305
9.3%
4 277
8.5%
5 275
8.4%
7 256
7.8%
8 249
7.6%
9 246
7.5%
6 244
7.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3272
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 490
15.0%
1 374
11.4%
2 355
10.8%
3 305
9.3%
4 277
8.5%
5 275
8.4%
7 256
7.8%
8 249
7.6%
9 246
7.5%
6 244
7.5%
Distinct531
Distinct (%)83.0%
Missing360
Missing (%)36.0%
Memory size50.0 KiB
2023-12-09T23:30:04.316641image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length8
Median length5
Mean length4.84375
Min length1

Characters and Unicode

Total characters3100
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique444 ?
Unique (%)69.4%

Sample

1st row21.46
2nd row1.11
3rd row1.09
4th row86.1
5th row15.8
ValueCountFrequency (%)
0 8
 
1.2%
7.02 5
 
0.8%
10.21 4
 
0.6%
0.91 4
 
0.6%
6.08 3
 
0.5%
22.18 3
 
0.5%
0.83 3
 
0.5%
62.84 3
 
0.5%
0.68 3
 
0.5%
25.54 3
 
0.5%
Other values (521) 601
93.9%
2023-12-09T23:30:04.916379image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 626
20.2%
1 368
11.9%
2 282
9.1%
3 268
8.6%
4 255
8.2%
6 239
 
7.7%
9 230
 
7.4%
5 226
 
7.3%
8 217
 
7.0%
7 208
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2474
79.8%
Other Punctuation 626
 
20.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 368
14.9%
2 282
11.4%
3 268
10.8%
4 255
10.3%
6 239
9.7%
9 230
9.3%
5 226
9.1%
8 217
8.8%
7 208
8.4%
0 181
7.3%
Other Punctuation
ValueCountFrequency (%)
. 626
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3100
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 626
20.2%
1 368
11.9%
2 282
9.1%
3 268
8.6%
4 255
8.2%
6 239
 
7.7%
9 230
 
7.4%
5 226
 
7.3%
8 217
 
7.0%
7 208
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3100
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 626
20.2%
1 368
11.9%
2 282
9.1%
3 268
8.6%
4 255
8.2%
6 239
 
7.7%
9 230
 
7.4%
5 226
 
7.3%
8 217
 
7.0%
7 208
 
6.7%
Distinct4
Distinct (%)100.0%
Missing996
Missing (%)99.6%
Memory size31.5 KiB
2023-12-09T23:30:05.105565image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length5.5
Mean length5.5
Min length5

Characters and Unicode

Total characters22
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st row1003.2
2nd row521.6
3rd row404.3
4th row2492.9
ValueCountFrequency (%)
404.3 1
25.0%
1003.2 1
25.0%
2492.9 1
25.0%
521.6 1
25.0%
2023-12-09T23:30:05.395354image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 4
18.2%
2 4
18.2%
4 3
13.6%
0 3
13.6%
3 2
9.1%
1 2
9.1%
9 2
9.1%
5 1
 
4.5%
6 1
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 18
81.8%
Other Punctuation 4
 
18.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 4
22.2%
4 3
16.7%
0 3
16.7%
3 2
11.1%
1 2
11.1%
9 2
11.1%
5 1
 
5.6%
6 1
 
5.6%
Other Punctuation
ValueCountFrequency (%)
. 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 22
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 4
18.2%
2 4
18.2%
4 3
13.6%
0 3
13.6%
3 2
9.1%
1 2
9.1%
9 2
9.1%
5 1
 
4.5%
6 1
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 4
18.2%
2 4
18.2%
4 3
13.6%
0 3
13.6%
3 2
9.1%
1 2
9.1%
9 2
9.1%
5 1
 
4.5%
6 1
 
4.5%
Distinct14
Distinct (%)50.0%
Missing972
Missing (%)97.2%
Memory size32.1 KiB
2023-12-09T23:30:05.541359image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.428571429
Min length1

Characters and Unicode

Total characters40
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)28.6%

Sample

1st row58
2nd row9
3rd row1
4th row9
5th row1
ValueCountFrequency (%)
1 9
32.1%
9 3
 
10.7%
73 2
 
7.1%
19 2
 
7.1%
21 2
 
7.1%
3 2
 
7.1%
8 1
 
3.6%
4 1
 
3.6%
67 1
 
3.6%
35 1
 
3.6%
Other values (4) 4
14.3%
2023-12-09T23:30:05.813897image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
35.0%
3 6
15.0%
9 5
 
12.5%
7 5
 
12.5%
2 3
 
7.5%
5 3
 
7.5%
8 2
 
5.0%
4 1
 
2.5%
6 1
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 40
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
35.0%
3 6
15.0%
9 5
 
12.5%
7 5
 
12.5%
2 3
 
7.5%
5 3
 
7.5%
8 2
 
5.0%
4 1
 
2.5%
6 1
 
2.5%

Most occurring scripts

ValueCountFrequency (%)
Common 40
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
35.0%
3 6
15.0%
9 5
 
12.5%
7 5
 
12.5%
2 3
 
7.5%
5 3
 
7.5%
8 2
 
5.0%
4 1
 
2.5%
6 1
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 40
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 14
35.0%
3 6
15.0%
9 5
 
12.5%
7 5
 
12.5%
2 3
 
7.5%
5 3
 
7.5%
8 2
 
5.0%
4 1
 
2.5%
6 1
 
2.5%

irrigated_area_ft
Text

MISSING 

Distinct11
Distinct (%)13.8%
Missing920
Missing (%)92.0%
Memory size33.4 KiB
2023-12-09T23:30:05.961461image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length1
Mean length1.5125
Min length1

Characters and Unicode

Total characters121
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)11.2%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 69
86.2%
40206 2
 
2.5%
5000 1
 
1.2%
300 1
 
1.2%
42924 1
 
1.2%
1000 1
 
1.2%
18592.6 1
 
1.2%
33736 1
 
1.2%
1200 1
 
1.2%
30000 1
 
1.2%
2023-12-09T23:30:06.227693image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 90
74.4%
2 7
 
5.8%
6 5
 
4.1%
3 5
 
4.1%
4 4
 
3.3%
1 3
 
2.5%
5 2
 
1.7%
9 2
 
1.7%
8 1
 
0.8%
. 1
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 120
99.2%
Other Punctuation 1
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 90
75.0%
2 7
 
5.8%
6 5
 
4.2%
3 5
 
4.2%
4 4
 
3.3%
1 3
 
2.5%
5 2
 
1.7%
9 2
 
1.7%
8 1
 
0.8%
7 1
 
0.8%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 121
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 90
74.4%
2 7
 
5.8%
6 5
 
4.1%
3 5
 
4.1%
4 4
 
3.3%
1 3
 
2.5%
5 2
 
1.7%
9 2
 
1.7%
8 1
 
0.8%
. 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 121
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 90
74.4%
2 7
 
5.8%
6 5
 
4.1%
3 5
 
4.1%
4 4
 
3.3%
1 3
 
2.5%
5 2
 
1.7%
9 2
 
1.7%
8 1
 
0.8%
. 1
 
0.8%
Distinct4
Distinct (%)100.0%
Missing996
Missing (%)99.6%
Memory size31.6 KiB
2023-12-09T23:30:06.423902image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length23
Median length23
Mean length23
Min length23

Characters and Unicode

Total characters92
Distinct characters12
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st row2017-04-21T00:00:00.000
2nd row2017-09-05T00:00:00.000
3rd row2015-07-13T00:00:00.000
4th row2011-12-19T00:00:00.000
ValueCountFrequency (%)
2011-12-19t00:00:00.000 1
25.0%
2015-07-13t00:00:00.000 1
25.0%
2017-09-05t00:00:00.000 1
25.0%
2017-04-21t00:00:00.000 1
25.0%
2023-12-09T23:30:06.719317image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 44
47.8%
1 9
 
9.8%
- 8
 
8.7%
: 8
 
8.7%
2 6
 
6.5%
T 4
 
4.3%
. 4
 
4.3%
7 3
 
3.3%
9 2
 
2.2%
5 2
 
2.2%
Other values (2) 2
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 68
73.9%
Other Punctuation 12
 
13.0%
Dash Punctuation 8
 
8.7%
Uppercase Letter 4
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 44
64.7%
1 9
 
13.2%
2 6
 
8.8%
7 3
 
4.4%
9 2
 
2.9%
5 2
 
2.9%
3 1
 
1.5%
4 1
 
1.5%
Other Punctuation
ValueCountFrequency (%)
: 8
66.7%
. 4
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Uppercase Letter
ValueCountFrequency (%)
T 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 88
95.7%
Latin 4
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 44
50.0%
1 9
 
10.2%
- 8
 
9.1%
: 8
 
9.1%
2 6
 
6.8%
. 4
 
4.5%
7 3
 
3.4%
9 2
 
2.3%
5 2
 
2.3%
3 1
 
1.1%
Latin
ValueCountFrequency (%)
T 4
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 92
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 44
47.8%
1 9
 
9.8%
- 8
 
8.7%
: 8
 
8.7%
2 6
 
6.5%
T 4
 
4.3%
. 4
 
4.3%
7 3
 
3.3%
9 2
 
2.2%
5 2
 
2.2%
Other values (2) 2
 
2.2%

third_party_certification_1
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)25.0%
Missing996
Missing (%)99.6%
Memory size31.5 KiB
2023-12-09T23:30:06.845589image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters16
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowLEED
2nd rowLEED
3rd rowLEED
4th rowLEED
ValueCountFrequency (%)
leed 4
100.0%
2023-12-09T23:30:07.073377image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 8
50.0%
L 4
25.0%
D 4
25.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 16
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 8
50.0%
L 4
25.0%
D 4
25.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 16
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 8
50.0%
L 4
25.0%
D 4
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
E 8
50.0%
L 4
25.0%
D 4
25.0%
Distinct4
Distinct (%)100.0%
Missing996
Missing (%)99.6%
Memory size31.6 KiB
2023-12-09T23:30:07.263252image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length23
Median length23
Mean length23
Min length23

Characters and Unicode

Total characters92
Distinct characters11
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st row2017-07-19T00:00:00.000
2nd row2017-09-05T00:00:00.000
3rd row2015-07-13T00:00:00.000
4th row2011-12-19T00:00:00.000
ValueCountFrequency (%)
2011-12-19t00:00:00.000 1
25.0%
2015-07-13t00:00:00.000 1
25.0%
2017-07-19t00:00:00.000 1
25.0%
2017-09-05t00:00:00.000 1
25.0%
2023-12-09T23:30:07.564973image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 44
47.8%
1 9
 
9.8%
- 8
 
8.7%
: 8
 
8.7%
2 5
 
5.4%
T 4
 
4.3%
. 4
 
4.3%
7 4
 
4.3%
9 3
 
3.3%
5 2
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 68
73.9%
Other Punctuation 12
 
13.0%
Dash Punctuation 8
 
8.7%
Uppercase Letter 4
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 44
64.7%
1 9
 
13.2%
2 5
 
7.4%
7 4
 
5.9%
9 3
 
4.4%
5 2
 
2.9%
3 1
 
1.5%
Other Punctuation
ValueCountFrequency (%)
: 8
66.7%
. 4
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Uppercase Letter
ValueCountFrequency (%)
T 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 88
95.7%
Latin 4
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 44
50.0%
1 9
 
10.2%
- 8
 
9.1%
: 8
 
9.1%
2 5
 
5.7%
. 4
 
4.5%
7 4
 
4.5%
9 3
 
3.4%
5 2
 
2.3%
3 1
 
1.1%
Latin
ValueCountFrequency (%)
T 4
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 92
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 44
47.8%
1 9
 
9.8%
- 8
 
8.7%
: 8
 
8.7%
2 5
 
5.4%
T 4
 
4.3%
. 4
 
4.3%
7 4
 
4.3%
9 3
 
3.3%
5 2
 
2.2%
Distinct7
Distinct (%)77.8%
Missing991
Missing (%)99.1%
Memory size31.6 KiB
2023-12-09T23:30:07.732826image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length6
Mean length4.555555556
Min length1

Characters and Unicode

Total characters41
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)55.6%

Sample

1st row2.1016
2nd row2
3rd row2
4th row0.55
5th row1.60085
ValueCountFrequency (%)
1.60085 2
22.2%
2 2
22.2%
2.1016 1
11.1%
2.43828 1
11.1%
2.21053 1
11.1%
0 1
11.1%
0.55 1
11.1%
2023-12-09T23:30:08.017166image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 8
19.5%
2 7
17.1%
. 6
14.6%
1 5
12.2%
5 5
12.2%
8 4
9.8%
6 3
 
7.3%
3 2
 
4.9%
4 1
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 35
85.4%
Other Punctuation 6
 
14.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 8
22.9%
2 7
20.0%
1 5
14.3%
5 5
14.3%
8 4
11.4%
6 3
 
8.6%
3 2
 
5.7%
4 1
 
2.9%
Other Punctuation
ValueCountFrequency (%)
. 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 41
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 8
19.5%
2 7
17.1%
. 6
14.6%
1 5
12.2%
5 5
12.2%
8 4
9.8%
6 3
 
7.3%
3 2
 
4.9%
4 1
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 41
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 8
19.5%
2 7
17.1%
. 6
14.6%
1 5
12.2%
5 5
12.2%
8 4
9.8%
6 3
 
7.3%
3 2
 
4.9%
4 1
 
2.4%

convenience_store_with_gas
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1000
Missing (%)100.0%
Memory size7.9 KiB

convenience_store_with_gas_1
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1000
Missing (%)100.0%
Memory size7.9 KiB
Distinct15
Distinct (%)83.3%
Missing982
Missing (%)98.2%
Memory size31.9 KiB
2023-12-09T23:30:08.206882image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length7
Mean length5.944444444
Min length1

Characters and Unicode

Total characters107
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)72.2%

Sample

1st row2.30468
2nd row2.30468
3rd row4.31112
4th row2.30468
5th row1.6129
ValueCountFrequency (%)
2.30468 3
16.7%
2 2
 
11.1%
1.1566 1
 
5.6%
5.82236 1
 
5.6%
5.54959 1
 
5.6%
2.15222 1
 
5.6%
4.31112 1
 
5.6%
3.72358 1
 
5.6%
2.77545 1
 
5.6%
1.6129 1
 
5.6%
Other values (5) 5
27.8%
2023-12-09T23:30:08.537229image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 16
15.0%
2 15
14.0%
3 13
12.1%
4 12
11.2%
1 12
11.2%
5 10
9.3%
6 9
8.4%
8 6
 
5.6%
0 5
 
4.7%
9 5
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 91
85.0%
Other Punctuation 16
 
15.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 15
16.5%
3 13
14.3%
4 12
13.2%
1 12
13.2%
5 10
11.0%
6 9
9.9%
8 6
 
6.6%
0 5
 
5.5%
9 5
 
5.5%
7 4
 
4.4%
Other Punctuation
ValueCountFrequency (%)
. 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 107
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 16
15.0%
2 15
14.0%
3 13
12.1%
4 12
11.2%
1 12
11.2%
5 10
9.3%
6 9
8.4%
8 6
 
5.6%
0 5
 
4.7%
9 5
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 107
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 16
15.0%
2 15
14.0%
3 13
12.1%
4 12
11.2%
1 12
11.2%
5 10
9.3%
6 9
8.4%
8 6
 
5.6%
0 5
 
4.7%
9 5
 
4.7%
Distinct7
Distinct (%)43.8%
Missing984
Missing (%)98.4%
Memory size31.9 KiB
2023-12-09T23:30:08.697979image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.75
Min length5

Characters and Unicode

Total characters92
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)37.5%

Sample

1st row1.18209
2nd row0.84818
3rd row1.04619
4th row1.584
5th row1.63218
ValueCountFrequency (%)
1.584 10
62.5%
1.04619 1
 
6.2%
2.38947 1
 
6.2%
1.18209 1
 
6.2%
0.84818 1
 
6.2%
1.52671 1
 
6.2%
1.63218 1
 
6.2%
2023-12-09T23:30:08.986302image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 19
20.7%
. 16
17.4%
8 16
17.4%
4 13
14.1%
5 11
12.0%
2 4
 
4.3%
0 3
 
3.3%
6 3
 
3.3%
9 3
 
3.3%
3 2
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 76
82.6%
Other Punctuation 16
 
17.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 19
25.0%
8 16
21.1%
4 13
17.1%
5 11
14.5%
2 4
 
5.3%
0 3
 
3.9%
6 3
 
3.9%
9 3
 
3.9%
3 2
 
2.6%
7 2
 
2.6%
Other Punctuation
ValueCountFrequency (%)
. 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 92
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 19
20.7%
. 16
17.4%
8 16
17.4%
4 13
14.1%
5 11
12.0%
2 4
 
4.3%
0 3
 
3.3%
6 3
 
3.3%
9 3
 
3.3%
3 2
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 92
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 19
20.7%
. 16
17.4%
8 16
17.4%
4 13
14.1%
5 11
12.0%
2 4
 
4.3%
0 3
 
3.3%
6 3
 
3.3%
9 3
 
3.3%
3 2
 
2.2%
Distinct779
Distinct (%)82.1%
Missing51
Missing (%)5.1%
Memory size75.9 KiB
2023-12-09T23:30:09.416809image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length23
Median length23
Mean length23
Min length23

Characters and Unicode

Total characters21827
Distinct characters20
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique682 ?
Unique (%)71.9%

Sample

1st row01/26/2018 02:37 PM EST
2nd row02/14/2018 02:22 PM EST
3rd row01/24/2018 04:24 PM EST
4th row02/07/2018 12:05 PM EST
5th row01/31/2018 03:20 PM EST
ValueCountFrequency (%)
edt 689
18.2%
pm 577
 
15.2%
am 372
 
9.8%
est 260
 
6.8%
03/26/2018 63
 
1.7%
03/16/2018 63
 
1.7%
03/23/2018 61
 
1.6%
04/03/2018 46
 
1.2%
03/20/2018 43
 
1.1%
03/30/2018 43
 
1.1%
Other values (483) 1579
41.6%
2023-12-09T23:30:09.965462image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3117
14.3%
2847
13.0%
1 2187
10.0%
2 2058
9.4%
/ 1898
8.7%
3 1235
 
5.7%
8 1142
 
5.2%
T 949
 
4.3%
: 949
 
4.3%
M 949
 
4.3%
Other values (10) 4496
20.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11388
52.2%
Uppercase Letter 4745
21.7%
Space Separator 2847
 
13.0%
Other Punctuation 2847
 
13.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3117
27.4%
1 2187
19.2%
2 2058
18.1%
3 1235
 
10.8%
8 1142
 
10.0%
4 515
 
4.5%
5 433
 
3.8%
9 294
 
2.6%
6 260
 
2.3%
7 147
 
1.3%
Uppercase Letter
ValueCountFrequency (%)
T 949
20.0%
M 949
20.0%
E 949
20.0%
D 689
14.5%
P 577
12.2%
A 372
 
7.8%
S 260
 
5.5%
Other Punctuation
ValueCountFrequency (%)
/ 1898
66.7%
: 949
33.3%
Space Separator
ValueCountFrequency (%)
2847
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 17082
78.3%
Latin 4745
 
21.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3117
18.2%
2847
16.7%
1 2187
12.8%
2 2058
12.0%
/ 1898
11.1%
3 1235
 
7.2%
8 1142
 
6.7%
: 949
 
5.6%
4 515
 
3.0%
5 433
 
2.5%
Other values (3) 701
 
4.1%
Latin
ValueCountFrequency (%)
T 949
20.0%
M 949
20.0%
E 949
20.0%
D 689
14.5%
P 577
12.2%
A 372
 
7.8%
S 260
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21827
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3117
14.3%
2847
13.0%
1 2187
10.0%
2 2058
9.4%
/ 1898
8.7%
3 1235
 
5.7%
8 1142
 
5.2%
T 949
 
4.3%
: 949
 
4.3%
M 949
 
4.3%
Other values (10) 4496
20.6%
Distinct694
Distinct (%)79.4%
Missing126
Missing (%)12.6%
Memory size72.3 KiB
2023-12-09T23:30:10.388875image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length23
Median length23
Mean length23
Min length23

Characters and Unicode

Total characters20102
Distinct characters20
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique591 ?
Unique (%)67.6%

Sample

1st row01/26/2018 02:37 PM EST
2nd row02/14/2018 02:12 PM EST
3rd row02/06/2018 12:41 PM EST
4th row01/31/2018 03:00 PM EST
5th row01/31/2018 03:27 PM EST
ValueCountFrequency (%)
pm 530
 
15.2%
edt 530
 
15.2%
am 344
 
9.8%
est 344
 
9.8%
03/16/2018 61
 
1.7%
03/26/2018 57
 
1.6%
03/12/2018 41
 
1.2%
03/23/2018 34
 
1.0%
03/13/2018 34
 
1.0%
03/08/2018 32
 
0.9%
Other values (448) 1489
42.6%
2023-12-09T23:30:10.916754image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2934
14.6%
2622
13.0%
1 2038
10.1%
2 1864
9.3%
/ 1748
8.7%
3 1069
 
5.3%
8 1061
 
5.3%
T 874
 
4.3%
: 874
 
4.3%
M 874
 
4.3%
Other values (10) 4144
20.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10488
52.2%
Uppercase Letter 4370
21.7%
Space Separator 2622
 
13.0%
Other Punctuation 2622
 
13.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2934
28.0%
1 2038
19.4%
2 1864
17.8%
3 1069
 
10.2%
8 1061
 
10.1%
4 452
 
4.3%
5 358
 
3.4%
6 266
 
2.5%
9 260
 
2.5%
7 186
 
1.8%
Uppercase Letter
ValueCountFrequency (%)
T 874
20.0%
M 874
20.0%
E 874
20.0%
D 530
12.1%
P 530
12.1%
S 344
 
7.9%
A 344
 
7.9%
Other Punctuation
ValueCountFrequency (%)
/ 1748
66.7%
: 874
33.3%
Space Separator
ValueCountFrequency (%)
2622
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15732
78.3%
Latin 4370
 
21.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2934
18.6%
2622
16.7%
1 2038
13.0%
2 1864
11.8%
/ 1748
11.1%
3 1069
 
6.8%
8 1061
 
6.7%
: 874
 
5.6%
4 452
 
2.9%
5 358
 
2.3%
Other values (3) 712
 
4.5%
Latin
ValueCountFrequency (%)
T 874
20.0%
M 874
20.0%
E 874
20.0%
D 530
12.1%
P 530
12.1%
S 344
 
7.9%
A 344
 
7.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20102
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2934
14.6%
2622
13.0%
1 2038
10.1%
2 1864
9.3%
/ 1748
8.7%
3 1069
 
5.3%
8 1061
 
5.3%
T 874
 
4.3%
: 874
 
4.3%
M 874
 
4.3%
Other values (10) 4144
20.6%
Distinct590
Distinct (%)77.3%
Missing237
Missing (%)23.7%
Memory size67.1 KiB
2023-12-09T23:30:11.317876image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length23
Median length23
Mean length23
Min length23

Characters and Unicode

Total characters17549
Distinct characters20
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique489 ?
Unique (%)64.1%

Sample

1st row01/26/2018 02:13 PM EST
2nd row01/24/2018 04:23 PM EST
3rd row02/07/2018 11:40 AM EST
4th row01/31/2018 03:01 PM EST
5th row02/13/2018 03:48 PM EST
ValueCountFrequency (%)
pm 471
 
15.4%
edt 469
 
15.4%
est 294
 
9.6%
am 292
 
9.6%
03/26/2018 52
 
1.7%
03/12/2018 44
 
1.4%
03/23/2018 42
 
1.4%
03/20/2018 41
 
1.3%
03/16/2018 36
 
1.2%
03/14/2018 31
 
1.0%
Other values (427) 1280
41.9%
2023-12-09T23:30:11.837152image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2566
14.6%
2289
13.0%
1 1751
10.0%
2 1696
9.7%
/ 1526
8.7%
8 943
 
5.4%
3 942
 
5.4%
T 763
 
4.3%
E 763
 
4.3%
M 763
 
4.3%
Other values (10) 3547
20.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9156
52.2%
Uppercase Letter 3815
21.7%
Space Separator 2289
 
13.0%
Other Punctuation 2289
 
13.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2566
28.0%
1 1751
19.1%
2 1696
18.5%
8 943
 
10.3%
3 942
 
10.3%
4 392
 
4.3%
5 294
 
3.2%
9 221
 
2.4%
6 199
 
2.2%
7 152
 
1.7%
Uppercase Letter
ValueCountFrequency (%)
T 763
20.0%
E 763
20.0%
M 763
20.0%
P 471
12.3%
D 469
12.3%
S 294
 
7.7%
A 292
 
7.7%
Other Punctuation
ValueCountFrequency (%)
/ 1526
66.7%
: 763
33.3%
Space Separator
ValueCountFrequency (%)
2289
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13734
78.3%
Latin 3815
 
21.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2566
18.7%
2289
16.7%
1 1751
12.7%
2 1696
12.3%
/ 1526
11.1%
8 943
 
6.9%
3 942
 
6.9%
: 763
 
5.6%
4 392
 
2.9%
5 294
 
2.1%
Other values (3) 572
 
4.2%
Latin
ValueCountFrequency (%)
T 763
20.0%
E 763
20.0%
M 763
20.0%
P 471
12.3%
D 469
12.3%
S 294
 
7.7%
A 292
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17549
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2566
14.6%
2289
13.0%
1 1751
10.0%
2 1696
9.7%
/ 1526
8.7%
8 943
 
5.4%
3 942
 
5.4%
T 763
 
4.3%
E 763
 
4.3%
M 763
 
4.3%
Other values (10) 3547
20.2%
Distinct313
Distinct (%)85.1%
Missing632
Missing (%)63.2%
Memory size48.6 KiB
2023-12-09T23:30:12.140659image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length23
Median length23
Mean length23
Min length23

Characters and Unicode

Total characters8464
Distinct characters20
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique273 ?
Unique (%)74.2%

Sample

1st row01/25/2018 03:17 PM EST
2nd row02/14/2018 02:16 PM EST
3rd row02/14/2018 05:42 PM EST
4th row02/13/2018 04:10 PM EST
5th row02/16/2018 11:16 AM EST
ValueCountFrequency (%)
pm 226
 
15.4%
edt 213
 
14.5%
est 155
 
10.5%
am 142
 
9.6%
03/23/2018 24
 
1.6%
03/28/2018 21
 
1.4%
03/15/2018 20
 
1.4%
03/20/2018 19
 
1.3%
03/29/2018 18
 
1.2%
02/21/2018 17
 
1.2%
Other values (298) 617
41.9%
2023-12-09T23:30:12.567594image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1165
13.8%
1104
13.0%
1 899
10.6%
2 855
10.1%
/ 736
8.7%
8 463
 
5.5%
3 429
 
5.1%
M 368
 
4.3%
T 368
 
4.3%
: 368
 
4.3%
Other values (10) 1709
20.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4416
52.2%
Uppercase Letter 1840
21.7%
Space Separator 1104
 
13.0%
Other Punctuation 1104
 
13.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1165
26.4%
1 899
20.4%
2 855
19.4%
8 463
 
10.5%
3 429
 
9.7%
4 217
 
4.9%
5 137
 
3.1%
9 102
 
2.3%
6 90
 
2.0%
7 59
 
1.3%
Uppercase Letter
ValueCountFrequency (%)
M 368
20.0%
T 368
20.0%
E 368
20.0%
P 226
12.3%
D 213
11.6%
S 155
8.4%
A 142
 
7.7%
Other Punctuation
ValueCountFrequency (%)
/ 736
66.7%
: 368
33.3%
Space Separator
ValueCountFrequency (%)
1104
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6624
78.3%
Latin 1840
 
21.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1165
17.6%
1104
16.7%
1 899
13.6%
2 855
12.9%
/ 736
11.1%
8 463
 
7.0%
3 429
 
6.5%
: 368
 
5.6%
4 217
 
3.3%
5 137
 
2.1%
Other values (3) 251
 
3.8%
Latin
ValueCountFrequency (%)
M 368
20.0%
T 368
20.0%
E 368
20.0%
P 226
12.3%
D 213
11.6%
S 155
8.4%
A 142
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8464
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1165
13.8%
1104
13.0%
1 899
10.6%
2 855
10.1%
/ 736
8.7%
8 463
 
5.5%
3 429
 
5.1%
M 368
 
4.3%
T 368
 
4.3%
: 368
 
4.3%
Other values (10) 1709
20.2%
Distinct406
Distinct (%)59.7%
Missing320
Missing (%)32.0%
Memory size63.2 KiB
2023-12-09T23:30:12.984467image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length23
Median length23
Mean length23
Min length23

Characters and Unicode

Total characters15640
Distinct characters20
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique283 ?
Unique (%)41.6%

Sample

1st row02/14/2018 02:22 PM EST
2nd row01/24/2018 04:24 PM EST
3rd row02/07/2018 12:05 PM EST
4th row01/31/2018 03:20 PM EST
5th row01/31/2018 03:46 PM EST
ValueCountFrequency (%)
pm 411
15.1%
est 406
14.9%
edt 274
 
10.1%
am 269
 
9.9%
02/13/2018 220
 
8.1%
03/13/2018 38
 
1.4%
03/30/2018 29
 
1.1%
03/16/2018 28
 
1.0%
03/22/2018 24
 
0.9%
03/23/2018 20
 
0.7%
Other values (325) 1001
36.8%
2023-12-09T23:30:13.549811image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2043
13.1%
2040
13.0%
1 1827
11.7%
2 1710
10.9%
/ 1360
8.7%
3 854
 
5.5%
8 811
 
5.2%
T 680
 
4.3%
E 680
 
4.3%
M 680
 
4.3%
Other values (10) 2955
18.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8160
52.2%
Uppercase Letter 3400
21.7%
Space Separator 2040
 
13.0%
Other Punctuation 2040
 
13.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2043
25.0%
1 1827
22.4%
2 1710
21.0%
3 854
10.5%
8 811
 
9.9%
4 306
 
3.8%
5 239
 
2.9%
9 167
 
2.0%
6 123
 
1.5%
7 80
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
T 680
20.0%
E 680
20.0%
M 680
20.0%
P 411
12.1%
S 406
11.9%
D 274
8.1%
A 269
 
7.9%
Other Punctuation
ValueCountFrequency (%)
/ 1360
66.7%
: 680
33.3%
Space Separator
ValueCountFrequency (%)
2040
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12240
78.3%
Latin 3400
 
21.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2043
16.7%
2040
16.7%
1 1827
14.9%
2 1710
14.0%
/ 1360
11.1%
3 854
7.0%
8 811
 
6.6%
: 680
 
5.6%
4 306
 
2.5%
5 239
 
2.0%
Other values (3) 370
 
3.0%
Latin
ValueCountFrequency (%)
T 680
20.0%
E 680
20.0%
M 680
20.0%
P 411
12.1%
S 406
11.9%
D 274
8.1%
A 269
 
7.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15640
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2043
13.1%
2040
13.0%
1 1827
11.7%
2 1710
10.9%
/ 1360
8.7%
3 854
 
5.5%
8 811
 
5.2%
T 680
 
4.3%
E 680
 
4.3%
M 680
 
4.3%
Other values (10) 2955
18.9%

borough
Text

MISSING 

Distinct5
Distinct (%)0.5%
Missing58
Missing (%)5.8%
Memory size61.3 KiB
2023-12-09T23:30:13.728043image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length9
Median length8
Mean length7.496815287
Min length5

Characters and Unicode

Total characters7062
Distinct characters18
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMANHATTAN
2nd rowBRONX
3rd rowQUEENS
4th rowMANHATTAN
5th rowMANHATTAN
ValueCountFrequency (%)
manhattan 432
45.4%
bronx 206
21.6%
queens 149
 
15.7%
brooklyn 145
 
15.2%
staten 10
 
1.1%
is 10
 
1.1%
2023-12-09T23:30:14.030058image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 1374
19.5%
A 1306
18.5%
T 884
12.5%
O 496
 
7.0%
M 432
 
6.1%
H 432
 
6.1%
B 351
 
5.0%
R 351
 
5.0%
E 308
 
4.4%
X 206
 
2.9%
Other values (8) 922
13.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 7052
99.9%
Space Separator 10
 
0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 1374
19.5%
A 1306
18.5%
T 884
12.5%
O 496
 
7.0%
M 432
 
6.1%
H 432
 
6.1%
B 351
 
5.0%
R 351
 
5.0%
E 308
 
4.4%
X 206
 
2.9%
Other values (7) 912
12.9%
Space Separator
ValueCountFrequency (%)
10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 7052
99.9%
Common 10
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 1374
19.5%
A 1306
18.5%
T 884
12.5%
O 496
 
7.0%
M 432
 
6.1%
H 432
 
6.1%
B 351
 
5.0%
R 351
 
5.0%
E 308
 
4.4%
X 206
 
2.9%
Other values (7) 912
12.9%
Common
ValueCountFrequency (%)
10
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7062
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 1374
19.5%
A 1306
18.5%
T 884
12.5%
O 496
 
7.0%
M 432
 
6.1%
H 432
 
6.1%
B 351
 
5.0%
R 351
 
5.0%
E 308
 
4.4%
X 206
 
2.9%
Other values (8) 922
13.1%

latitude
Text

MISSING 

Distinct825
Distinct (%)87.6%
Missing58
Missing (%)5.8%
Memory size62.6 KiB
2023-12-09T23:30:14.438227image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length9
Median length9
Mean length8.907643312
Min length7

Characters and Unicode

Total characters8391
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique728 ?
Unique (%)77.3%

Sample

1st row40.765949
2nd row40.821209
3rd row40.736195
4th row40.74431
5th row40.709765
ValueCountFrequency (%)
40.768032 5
 
0.5%
40.768462 5
 
0.5%
40.620933 5
 
0.5%
40.7178 4
 
0.4%
40.752524 3
 
0.3%
40.752532 3
 
0.3%
40.870587 3
 
0.3%
40.606932 3
 
0.3%
40.727758 3
 
0.3%
40.722119 3
 
0.3%
Other values (815) 905
96.1%
2023-12-09T23:30:14.957429image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 1492
17.8%
0 1337
15.9%
7 960
11.4%
. 942
11.2%
8 684
8.2%
6 614
7.3%
5 590
 
7.0%
3 483
 
5.8%
2 452
 
5.4%
1 443
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7449
88.8%
Other Punctuation 942
 
11.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 1492
20.0%
0 1337
17.9%
7 960
12.9%
8 684
9.2%
6 614
8.2%
5 590
 
7.9%
3 483
 
6.5%
2 452
 
6.1%
1 443
 
5.9%
9 394
 
5.3%
Other Punctuation
ValueCountFrequency (%)
. 942
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8391
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 1492
17.8%
0 1337
15.9%
7 960
11.4%
. 942
11.2%
8 684
8.2%
6 614
7.3%
5 590
 
7.0%
3 483
 
5.8%
2 452
 
5.4%
1 443
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8391
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 1492
17.8%
0 1337
15.9%
7 960
11.4%
. 942
11.2%
8 684
8.2%
6 614
7.3%
5 590
 
7.0%
3 483
 
5.8%
2 452
 
5.4%
1 443
 
5.3%

longitude
Text

MISSING 

Distinct826
Distinct (%)87.7%
Missing58
Missing (%)5.8%
Memory size63.5 KiB
2023-12-09T23:30:15.335540image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length18
Median length10
Mean length9.897027601
Min length7

Characters and Unicode

Total characters9323
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique730 ?
Unique (%)77.5%

Sample

1st row-73.981073
2nd row-73.837894
3rd row-73.869956
4th row-73.988924
5th row-74.008765
ValueCountFrequency (%)
73.840864 5
 
0.5%
74.028454 5
 
0.5%
73.952436 5
 
0.5%
73.917949 4
 
0.4%
73.854069 3
 
0.3%
73.986383 3
 
0.3%
73.899501 3
 
0.3%
73.975124 3
 
0.3%
73.980033 3
 
0.3%
73.919203 3
 
0.3%
Other values (816) 905
96.1%
2023-12-09T23:30:15.836529image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 1440
15.4%
3 1295
13.9%
9 1136
12.2%
- 942
10.1%
. 942
10.1%
8 776
8.3%
4 484
 
5.2%
6 477
 
5.1%
5 477
 
5.1%
0 471
 
5.1%
Other values (2) 883
9.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7439
79.8%
Dash Punctuation 942
 
10.1%
Other Punctuation 942
 
10.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 1440
19.4%
3 1295
17.4%
9 1136
15.3%
8 776
10.4%
4 484
 
6.5%
6 477
 
6.4%
5 477
 
6.4%
0 471
 
6.3%
1 445
 
6.0%
2 438
 
5.9%
Dash Punctuation
ValueCountFrequency (%)
- 942
100.0%
Other Punctuation
ValueCountFrequency (%)
. 942
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9323
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
7 1440
15.4%
3 1295
13.9%
9 1136
12.2%
- 942
10.1%
. 942
10.1%
8 776
8.3%
4 484
 
5.2%
6 477
 
5.1%
5 477
 
5.1%
0 471
 
5.1%
Other values (2) 883
9.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9323
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 1440
15.4%
3 1295
13.9%
9 1136
12.2%
- 942
10.1%
. 942
10.1%
8 776
8.3%
4 484
 
5.2%
6 477
 
5.1%
5 477
 
5.1%
0 471
 
5.1%
Other values (2) 883
9.5%

community_board
Text

MISSING 

Distinct58
Distinct (%)6.2%
Missing58
Missing (%)5.8%
Memory size57.1 KiB
2023-12-09T23:30:16.085332image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters2826
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)0.3%

Sample

1st row105
2nd row210
3rd row404
4th row105
5th row101
ValueCountFrequency (%)
105 160
 
17.0%
108 44
 
4.7%
104 37
 
3.9%
205 36
 
3.8%
107 36
 
3.8%
112 35
 
3.7%
106 33
 
3.5%
102 32
 
3.4%
407 32
 
3.4%
207 30
 
3.2%
Other values (48) 467
49.6%
2023-12-09T23:30:16.439838image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 776
27.5%
1 732
25.9%
2 356
12.6%
4 254
 
9.0%
5 243
 
8.6%
3 184
 
6.5%
7 105
 
3.7%
8 71
 
2.5%
6 62
 
2.2%
9 43
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2826
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 776
27.5%
1 732
25.9%
2 356
12.6%
4 254
 
9.0%
5 243
 
8.6%
3 184
 
6.5%
7 105
 
3.7%
8 71
 
2.5%
6 62
 
2.2%
9 43
 
1.5%

Most occurring scripts

ValueCountFrequency (%)
Common 2826
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 776
27.5%
1 732
25.9%
2 356
12.6%
4 254
 
9.0%
5 243
 
8.6%
3 184
 
6.5%
7 105
 
3.7%
8 71
 
2.5%
6 62
 
2.2%
9 43
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2826
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 776
27.5%
1 732
25.9%
2 356
12.6%
4 254
 
9.0%
5 243
 
8.6%
3 184
 
6.5%
7 105
 
3.7%
8 71
 
2.5%
6 62
 
2.2%
9 43
 
1.5%

council_district
Text

MISSING 

Distinct50
Distinct (%)5.3%
Missing58
Missing (%)5.8%
Memory size55.8 KiB
2023-12-09T23:30:16.665446image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length1.566878981
Min length1

Characters and Unicode

Total characters1476
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)0.3%

Sample

1st row4
2nd row13
3rd row25
4th row3
5th row1
ValueCountFrequency (%)
4 129
 
13.7%
3 98
 
10.4%
14 54
 
5.7%
1 42
 
4.5%
2 41
 
4.4%
10 36
 
3.8%
15 31
 
3.3%
6 31
 
3.3%
26 29
 
3.1%
13 28
 
3.0%
Other values (40) 423
44.9%
2023-12-09T23:30:17.007759image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 325
22.0%
4 312
21.1%
3 240
16.3%
2 171
11.6%
5 95
 
6.4%
0 82
 
5.6%
6 79
 
5.4%
9 70
 
4.7%
8 63
 
4.3%
7 39
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1476
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 325
22.0%
4 312
21.1%
3 240
16.3%
2 171
11.6%
5 95
 
6.4%
0 82
 
5.6%
6 79
 
5.4%
9 70
 
4.7%
8 63
 
4.3%
7 39
 
2.6%

Most occurring scripts

ValueCountFrequency (%)
Common 1476
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 325
22.0%
4 312
21.1%
3 240
16.3%
2 171
11.6%
5 95
 
6.4%
0 82
 
5.6%
6 79
 
5.4%
9 70
 
4.7%
8 63
 
4.3%
7 39
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1476
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 325
22.0%
4 312
21.1%
3 240
16.3%
2 171
11.6%
5 95
 
6.4%
0 82
 
5.6%
6 79
 
5.4%
9 70
 
4.7%
8 63
 
4.3%
7 39
 
2.6%

census_tract
Text

MISSING 

Distinct369
Distinct (%)39.2%
Missing58
Missing (%)5.8%
Memory size57.2 KiB
2023-12-09T23:30:17.506738image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.038216561
Min length1

Characters and Unicode

Total characters2862
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique163 ?
Unique (%)17.3%

Sample

1st row137
2nd row90
3rd row683
4th row58
5th row1502
ValueCountFrequency (%)
21001 16
 
1.7%
109 16
 
1.7%
19 15
 
1.6%
76 14
 
1.5%
113 14
 
1.5%
82 13
 
1.4%
219 12
 
1.3%
137 11
 
1.2%
9 11
 
1.2%
94 11
 
1.2%
Other values (359) 809
85.9%
2023-12-09T23:30:18.150195image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 602
21.0%
2 398
13.9%
0 332
11.6%
9 285
10.0%
3 261
9.1%
5 215
 
7.5%
7 210
 
7.3%
4 206
 
7.2%
6 200
 
7.0%
8 153
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2862
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 602
21.0%
2 398
13.9%
0 332
11.6%
9 285
10.0%
3 261
9.1%
5 215
 
7.5%
7 210
 
7.3%
4 206
 
7.2%
6 200
 
7.0%
8 153
 
5.3%

Most occurring scripts

ValueCountFrequency (%)
Common 2862
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 602
21.0%
2 398
13.9%
0 332
11.6%
9 285
10.0%
3 261
9.1%
5 215
 
7.5%
7 210
 
7.3%
4 206
 
7.2%
6 200
 
7.0%
8 153
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2862
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 602
21.0%
2 398
13.9%
0 332
11.6%
9 285
10.0%
3 261
9.1%
5 215
 
7.5%
7 210
 
7.3%
4 206
 
7.2%
6 200
 
7.0%
8 153
 
5.3%

nta
Text

MISSING 

Distinct138
Distinct (%)14.6%
Missing58
Missing (%)5.8%
Memory size73.7 KiB
2023-12-09T23:30:18.534029image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length50
Median length36
Mean length21.02229299
Min length6

Characters and Unicode

Total characters19803
Distinct characters53
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)3.3%

Sample

1st rowMidtown-Midtown South
2nd rowSoundview-Castle Hill-Clason Point-Harding Park
3rd rowElmhurst
4th rowHudson Yards-Chelsea-Flatiron-Union Square
5th rowBattery Park City-Lower Manhattan
ValueCountFrequency (%)
south 156
 
7.1%
midtown-midtown 121
 
5.5%
heights 83
 
3.8%
east 58
 
2.6%
square 58
 
2.6%
west 54
 
2.5%
north 50
 
2.3%
hill 47
 
2.1%
hudson 41
 
1.9%
yards-chelsea-flatiron-union 41
 
1.9%
Other values (181) 1480
67.6%
2023-12-09T23:30:19.095843image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 1514
 
7.6%
o 1438
 
7.3%
e 1428
 
7.2%
i 1289
 
6.5%
n 1281
 
6.5%
1247
 
6.3%
a 1114
 
5.6%
r 1097
 
5.5%
s 960
 
4.8%
l 839
 
4.2%
Other values (43) 7596
38.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 14831
74.9%
Uppercase Letter 2998
 
15.1%
Space Separator 1247
 
6.3%
Dash Punctuation 718
 
3.6%
Other Punctuation 9
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 1514
10.2%
o 1438
9.7%
e 1428
9.6%
i 1289
8.7%
n 1281
8.6%
a 1114
 
7.5%
r 1097
 
7.4%
s 960
 
6.5%
l 839
 
5.7%
d 726
 
4.9%
Other values (15) 3145
21.2%
Uppercase Letter
ValueCountFrequency (%)
M 449
15.0%
H 415
13.8%
S 351
11.7%
C 265
 
8.8%
B 216
 
7.2%
P 178
 
5.9%
W 151
 
5.0%
F 113
 
3.8%
U 104
 
3.5%
E 93
 
3.1%
Other values (14) 663
22.1%
Other Punctuation
ValueCountFrequency (%)
. 6
66.7%
' 3
33.3%
Space Separator
ValueCountFrequency (%)
1247
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 718
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 17829
90.0%
Common 1974
 
10.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 1514
 
8.5%
o 1438
 
8.1%
e 1428
 
8.0%
i 1289
 
7.2%
n 1281
 
7.2%
a 1114
 
6.2%
r 1097
 
6.2%
s 960
 
5.4%
l 839
 
4.7%
d 726
 
4.1%
Other values (39) 6143
34.5%
Common
ValueCountFrequency (%)
1247
63.2%
- 718
36.4%
. 6
 
0.3%
' 3
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19803
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 1514
 
7.6%
o 1438
 
7.3%
e 1428
 
7.2%
i 1289
 
6.5%
n 1281
 
6.5%
1247
 
6.3%
a 1114
 
5.6%
r 1097
 
5.5%
s 960
 
4.8%
l 839
 
4.2%
Other values (43) 7596
38.4%